11+ Marketing operations Jobs in Delhi, NCR and Gurgaon | Marketing operations Job openings in Delhi, NCR and Gurgaon

Below find the Job Description:-

Skill Set :

•  Hands-on experience with Advance Excel. 
• Team Handling experience
• The ability to generate excel reports & Validate them.
• Problem solving attitude
• Team Player

Job Responsibilities :

• Hand On experience in payments, stock management, Ecommerce Operations, Online Market Place, Cataloging (Procurement  Expert/ Inventory Management).
• Minimum 5 years of team handling experience
• Strong interaction with Internal & External teams.
• Managing Internal & External Merchants.
• Ticket & Escalation Management.
• Sale Support & getting higher discounts to improve sales

Strong Azure Databricks Engineer / Senior Data Engineer Profile

2

Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3

Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4

Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5

Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6

Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7

Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8

Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10

Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

Job Description – QA & Data Validation Engineer

Experience: 5–6 Years

Location: Pan India

Employment Type: Full-Time

Work Mode: Pan India / Remote or Hybrid as applicable

About the Role

We are looking for an experienced QA & Data Validation Engineer with 5–6 years of hands-on experience in data quality assurance, solution analysis, data validation, SQL, Python, PySpark, Azure Data Factory, Azure Synapse Analytics, and Power BI validation.

The ideal candidate will be responsible for validating large-scale data pipelines, performing source-to-target reconciliation, analyzing business rules, investigating data defects, and ensuring the accuracy, completeness, and consistency of data across source, staging, intermediate, and target systems.

The role requires strong analytical and problem-solving skills along with the ability to work closely with development, data engineering, business, and other stakeholders in an Agile delivery environment.

You will also contribute to the design, development, and maintenance of automated validation frameworks and utilities using Python, SQL, PySpark, Azure Data Factory, and Azure Synapse.

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Key Responsibilities

1. QA & Solution Analysis

- Analyze business and technical requirements to understand data processing and validation needs.

- Participate in requirement analysis sessions and clarify functional and technical requirements with stakeholders.

- Review solution designs, data flows, mapping documents, interface specifications, and business rules.

- Validate that implemented solutions meet defined business and technical requirements.

- Identify gaps, inconsistencies, ambiguities, and potential data quality issues during requirement and solution analysis.

- Translate business requirements into detailed test scenarios, test cases, and validation conditions.

- Perform end-to-end validation of data processing workflows.

- Ensure data is accurately processed from source systems through intermediate layers to final outputs.

- Validate business rules and transformation logic implemented within data pipelines.

2. Test Planning & Execution

- Prepare comprehensive test strategies, test plans, test scenarios, and test cases for data-intensive applications.

- Execute functional, integration, regression, system, and data validation testing.

- Perform positive and negative testing for different data processing scenarios.

- Validate data pipelines across multiple environments, including staging, testing, and production.

- Identify test data requirements and prepare appropriate datasets for validation.

- Execute SQL queries to validate data processing and transformation results.

- Document test results, observations, defects, and validation evidence.

- Track testing progress and communicate status, risks, issues, and dependencies to stakeholders.

3. Data Validation & Reconciliation

- Perform detailed source-to-target data validation and reconciliation.

- Validate source, intermediate, staging, and output datasets.

- Perform record count validation between source and target systems.

- Verify data completeness, consistency, accuracy, and integrity.

- Validate data transformations against defined business rules.

- Perform field-level and record-level comparisons.

- Validate data types, formats, precision, scale, and null handling.

- Verify schema structure, layout, column names, and column sequence.

- Validate mandatory and optional fields.

- Identify missing, duplicate, truncated, or incorrectly transformed records.

- Analyze invalid records, rejected records, and exception datasets.

- Verify exception and reject-handling mechanisms.

- Compare production and staging data to identify discrepancies.

- Perform reconciliation between files, databases, and reporting layers.

- Validate data across different processing stages and identify the root cause of discrepancies.

4. File & Data Processing Validation

- Validate large-scale datasets across multiple file formats.

- Perform validation of:

 - CSV files

 - Delimited files

 - Fixed-width files

 - Excel files

 - Database tables

 - Structured and semi-structured datasets

- Validate file layouts, headers, delimiters, record formats, and column sequences.

- Verify file-level and record-level counts.

- Analyze source, intermediate, and final output files.

- Validate file-to-database and database-to-file reconciliation.

- Identify incomplete, corrupted, malformed, or invalid records.

- Verify data movement and transformation between different storage locations.

- Validate Azure-to-AWS file transfer processes.

- Ensure transferred files are complete and match the expected source datasets.

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5. Defect Investigation & Root Cause Analysis

- Investigate data discrepancies and application/data pipeline defects.

- Perform detailed root cause analysis for data quality and validation failures.

- Analyze source data, transformation logic, pipeline execution, database records, and output datasets to identify defects.

- Collaborate with developers and data engineers to resolve identified issues.

- Reproduce defects and provide detailed technical evidence.

- Perform defect impact analysis.

- Conduct retesting and regression testing after defect resolution.

- Monitor recurring data quality issues and recommend preventive solutions.

- Maintain detailed defect documentation and validation results.

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6. Python Development & Automation

- Develop Python scripts and utilities for data validation and reconciliation.

- Design, develop, and maintain reusable data validation frameworks.

- Automate repetitive data comparison and validation activities.

- Build automated utilities for:

 - Record count validation

 - Data completeness checks

 - Schema validation

 - Column sequence validation

 - Source-to-target comparison

 - Duplicate detection

 - Exception identification

 - Data quality checks

 - Automated reporting

- Develop Python-based validation and reporting utilities.

- Optimize Python scripts for processing large datasets.

- Maintain and enhance existing automation frameworks.

- Implement reusable validation components to improve testing efficiency and coverage.

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7. SQL Development & Data Analysis

- Write complex SQL queries for data analysis and validation.

- Perform data extraction and comparison using SQL Server / SSMS.

- Validate source and target database records.

- Perform joins, aggregations, subqueries, CTEs, and analytical queries as required.

- Develop SQL queries to identify data mismatches, duplicates, missing records, and transformation issues.

- Validate database tables, schemas, columns, constraints, and relationships.

- Perform record count and reconciliation checks using SQL.

- Analyze SQL Server metrics databases.

- Validate data processing results against expected business rules.

- Troubleshoot data discrepancies using SQL queries.

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8. PySpark & Large-Scale Data Processing

- Develop and execute PySpark notebooks for large-scale dataset processing and validation.

- Analyze large volumes of structured and semi-structured data.

- Perform data transformation and validation using PySpark.

- Compare large source and target datasets efficiently.

- Implement data quality and reconciliation checks using PySpark.

- Analyze exception, reject, and invalid datasets.

- Optimize data validation processes for large datasets.

- Work with Azure Synapse notebooks and data processing environments.

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9. Azure Data Factory & Pipeline Testing

- Design and execute validation scenarios for Azure Data Factory (ADF) pipelines.

- Validate pipeline execution, data movement, transformations, and dependencies.

- Monitor pipeline runs and investigate failures.

- Validate source-to-target data movement through ADF.

- Develop and maintain test pipelines using Azure Data Factory.

- Verify pipeline parameters, triggers, activities, and execution results.

- Validate file ingestion and processing workflows.

- Perform end-to-end testing of data pipelines.

- Investigate pipeline-related data discrepancies and failures.

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10. Azure Synapse Analytics

- Work with Azure Synapse Analytics for data validation and analysis.

- Develop and execute Synapse notebooks using PySpark.

- Validate datasets processed through Synapse pipelines and notebooks.

- Perform data quality and reconciliation checks within Synapse environments.

- Analyze large-scale datasets and processing results.

- Validate data movement between Azure storage, Synapse, databases, and reporting systems.

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11. Azure Storage & Cosmos DB

- Validate data stored in Azure Storage Accounts and Containers.

- Verify file ingestion, processing, and output data.

- Perform file-level and content-level validation within Azure storage.

- Validate data processing workflows involving Azure Storage.

- Perform data validation in Azure Cosmos DB.

- Verify records, fields, formats, and data completeness within Cosmos DB.

- Investigate discrepancies between source files, Azure storage, databases, and Cosmos DB.

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12. AWS S3 & Azure-to-AWS Validation

- Validate files stored in AWS S3.

- Perform source-to-target validation for files transferred between Azure and AWS.

- Verify file counts, file names, sizes, formats, and record counts.

- Compare source files with transferred S3 files.

- Validate data integrity after cloud-to-cloud file transfers.

- Investigate missing, incomplete, duplicate, or corrupted files.

- Support end-to-end validation of Azure-to-AWS data movement processes.

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13. Metrics, Reporting & Power BI Validation

- Extract and validate source system metrics.

- Validate metrics stored in SQL Server databases.

- Perform reconciliation between source metrics, database metrics, and reporting outputs.

- Validate Power BI dashboards and reports against underlying source data.

- Verify report calculations, KPIs, measures, filters, and aggregations.

- Perform file-to-database-to-Power BI reconciliation.

- Validate data displayed in Power BI against SQL Server and source datasets.

- Identify discrepancies between backend data and dashboard results.

- Support reporting and analytics teams with data validation and troubleshooting.

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14. Production Support & Job Monitoring

- Monitor scheduled data processing jobs and pipelines.

- Perform production validation and health checks.

- Analyze production failures and data discrepancies.

- Support incident investigation and resolution.

- Compare production and staging environments to identify differences.

- Validate production data after deployments and pipeline executions.

- Monitor ECG jobs and provide support for job execution and data processing issues.

- Perform post-production validation and reconciliation.

- Communicate critical production issues and risks to relevant stakeholders.

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15. Agile Delivery & Stakeholder Collaboration

- Work effectively within an Agile/Scrum delivery environment.

- Participate in sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives.

- Collaborate with Business Analysts, Developers, Data Engineers, DevOps teams, Product Owners, and other stakeholders.

- Provide timely updates on testing progress and issues.

- Participate in requirement clarification and solution discussions.

- Support release planning and production deployment activities.

- Track work items and defects using Rally.

- Ensure testing activities are aligned with sprint and release timelines.

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Required Technical Skills

Mandatory Skills

- 5–6 years of experience in QA / Data Validation / Data Testing / Data Quality Engineering.

- Strong experience in SQL and data analysis.

- Hands-on experience with Python development and automation.

- Experience with PySpark and large-scale data processing.

- Strong experience with Azure Data Factory (ADF).

- Experience with Azure Synapse Analytics / Synapse Pipelines / Notebooks.

- Strong understanding of source-to-target data validation and reconciliation.

- Experience in data completeness, record count, schema, layout, and column validation.

- Experience in defect investigation and root cause analysis.

- Experience validating large datasets and multiple file formats.

- Experience with SQL Server / SSMS.

- Experience with Power BI dashboard/report validation.

- Strong understanding of data pipelines and ETL/ELT processes.

Cloud & Data Platform Experience

- Azure Data Factory

- Azure Synapse Analytics

- Azure Synapse Pipelines

- Azure Synapse Notebooks

- Azure Storage Accounts

- Azure Storage Containers

- Azure Cosmos DB

- Azure Privileged Identity Management (PIM)

- AWS S3

- Azure-to-AWS file transfer validation

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Preferred Skills

- Experience developing automated data validation frameworks.

- Experience building automated reporting and reconciliation utilities.

- Knowledge of ETL/ELT testing methodologies.

- Experience working with very large datasets.

- Experience in production data validation and support.

- Knowledge of cloud-based data platforms.

- Experience with Power BI data reconciliation.

- Experience working in Agile environments.

- Experience with Rally or similar Agile project management tools.

- Familiarity with Microsoft Copilot and AI-assisted productivity/automation tools.

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Key Responsibilities at a Glance

The successful candidate will be responsible for:

- Requirement analysis and clarification

- Business rule validation

- Test planning and execution

- Data quality and data validation

- Source-to-target reconciliation

- Record count and completeness validation

- Schema and layout validation

- Column sequence validation

- Exception and reject data analysis

- Production vs. staging comparison

- SQL-based data analysis

- Python automation

- PySpark development

- Azure Data Factory pipeline testing

- Azure Synapse validation

- Azure Storage validation

- Cosmos DB validation

- AWS S3 validation

- Azure-to-AWS file transfer validation

- Power BI dashboard validation

- SQL Server metrics validation

- Automated reporting

- Defect investigation and root cause analysis

- Production job monitoring and support

- Agile delivery and stakeholder collaboration

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Candidate Profile

We are looking for a detail-oriented, analytical, and technically strong QA/Data Validation professional who can work independently on complex data validation assignments.

The candidate should be comfortable working with large datasets, writing SQL queries, developing Python automation, analyzing PySpark datasets, validating cloud-based data pipelines, and troubleshooting data discrepancies across multiple systems.

Strong communication and stakeholder management skills are essential, as the role requires regular collaboration with technical and business teams.

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Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.

Experience

5–6 years of relevant professional experience in QA, Data Testing, Data Validation, ETL Testing, Data Quality, Data Engineering QA, or a similar role.

Location

Pan India

Employment Type

Full-Time

Keywords

QA Engineer, Data QA, Data Validation, Data Testing, ETL Testing, Data Quality, SQL, Python, PySpark, Azure Data Factory, ADF, Azure Synapse, Synapse Analytics, Synapse Pipelines, Azure Storage, Cosmos DB, AWS S3, Power BI, SQL Server, SSMS, Data Reconciliation, Source-to-Target Validation, Data Pipeline Testing, ETL QA, Automation Testing, Data Analytics, Root Cause Analysis, Agile, Rally, Cloud Data Testing, Data Engineering QA.

Job Description:

We are looking for a Customer Support Executive with at least 1 year of experience in an International Voice Process. The ideal candidate should have excellent communication skills, a customer-first approach, and the ability to resolve customer queries efficiently.

Key Responsibilities:

• Handle inbound/outbound customer calls.
• Resolve customer queries professionally and within SLA.
• Maintain accurate records of customer interactions.
• Ensure high customer satisfaction and service quality.

Requirements:

• Minimum 1 year of experience in an International Customer Support/Voice Process.
• Excellent verbal and written English communication skills.
• Graduate preferred.
• Willing to work in rotational/night shifts.
• Immediate joiners preferred.

Requirement:

1. Node Js min 2 yrs exp.
2. Database - MONGO, SQL, etc. min 2yrs experience with these.

3. Caching - REDIS, MEMCACHED etc

4. Message Queues - RABBIT MQ, Kafka, etc.

Location: Delhi (Work from office).
Package : Upto 12 LPA

Review Criteria

• Strong Product Manager Profiles
• 4+ years of product management experience, of which 2+ years in healthcare, pharmaceutical, life sciences, or AdTech domains
• Must have built or scaled products involving Data Science, Machine Learning, or AI
• Must have experience working end-to-end on product lifecycle — strategy, roadmap, development execution, stakeholder alignment, user research, product optimization, and adoption (0 to 1 product experience is preferred)
• Hands-on experience collaborating with engineering, data science, design, supply teams, and demand-side teams on parallel product initiatives
• Strong understanding of demand-side and supply-side mechanisms, programmatic advertising, data intelligence products, or marketplace platforms
• Experience in companies serving Healthcare Professionals (HCPs), Pharma, Life Sciences, or HealthTech advertising is a must
• Product companies (preferably in HealthTech)
• CTC includes 20% variable
• HealthTech exposure is a must (current or past experience)
• It’s an IC role

Preferred

• Experience working on AI-driven features such as predictive models, segmentation, personalization, or automated optimization.

Job Specific Criteria

• CV Attachment is mandatory
• What is your preferred location — Noida or Mumbai?
• If you’re based in Mumbai, are you comfortable traveling to the Noida office for one week each month?
• Are you available for an in-person interview for one of the rounds?
• Which HealthTech company(ies) you have worked for?

Role & Responsibilities

We are seeking a strategic and innovative Product Manager to lead the development and growth of our DataIQ and Marketplace products. This role is pivotal in driving the vision, strategy, and execution of our data intelligence and digital commerce platforms, ensuring they deliver exceptional value to our users and stakeholders.

Key Responsibilities-

Product Strategy & Vision:

• Define and articulate the product vision and roadmap for DataIQ and Marketplace, aligning with company objectives and market needs.
• Conduct market research and competitive analysis to identify opportunities for innovation and differentiation.
• Collaborate with stakeholders to prioritize features and initiatives that drive business impact and user satisfaction.

Product Development & Execution:

• Lead the end-to-end product development lifecycle, from ideation through to launch and iteration.
• Work closely with engineering, design, and data teams to deliver high-quality products on time and within scope.
• Develop clear and concise product documentation, including PRDs, user stories, and acceptance criteria.

User Experience & Enablement:

• Ensure a seamless and intuitive user experience across both DataIQ and Marketplace platforms.
• Collaborate with UX/UI teams to design user-centric interfaces that enhance engagement and usability.
• Provide training and support materials to enable users to maximize the value of our products.

Performance Monitoring & Optimization:

• Define and track key performance indicators (KPIs) to measure product success and inform decision-making.
• Analyze user feedback and product data to identify areas for improvement and optimization.
• Continuously iterate on product features and functionalities to enhance performance and user satisfaction.

Ideal Candidate

Experience & Skills:

• Bachelor's or Master's degree in Computer Science, Engineering, Business, or a related field.
• 4+ years of experience, with a proven track record in data intelligence or digital commerce products.
• Strong understanding of data analytics, cloud technologies, and e-commerce platforms.
• Excellent communication and collaboration skills, with the ability to work effectively across cross-functional teams.
• Analytical mindset with the ability to leverage data to drive product decisions.

Nice-to-Haves:

• Experience with machine learning or AI-driven product features.
• Familiarity with data governance and privacy regulations.
• Knowledge of marketplace dynamics and seller/buyer ecosystems.

Job Summary:

We are seeking a skilled MERN Stack Developer to join our dynamic development team. The ideal candidate will have hands-on experience in building modern web applications using MongoDB, Express.js, React.js, and Node.js. You will be responsible for designing and developing scalable, high-performance web applications and collaborating with cross-functional teams to deliver top-tier solutions.

Key Responsibilities:

• Develop and maintain responsive web applications using the MERN stack.
• Design, build, and maintain RESTful APIs and integrate third-party services.
• Collaborate with UI/UX designers, product managers, and other developers to deliver seamless user experiences.
• Optimize applications for performance and scalability.
• Write clean, maintainable, and efficient code.
• Participate in code reviews and provide constructive feedback.
• Debug and troubleshoot issues across the full stack.
• Implement security and data protection best practices.

About the Role

We are looking for a skilled PAM Consultant with strong expertise in implementing, managing, and optimizing Privileged Access Management solutions. The role involves working with enterprise-level security technologies such as BeyondTrust, Identity & Access Management (IAM), and Single Sign-On (SSO). The ideal candidate should have hands-on experience in deploying and supporting PAM platforms, integrating them with enterprise infrastructure, and ensuring compliance with security policies.

Key Responsibilities

• Design, implement, and maintain Privileged Access Management (PAM) solutions, primarily using BeyondTrust (Bomgar).
• Configure and administer PAM tools to manage privileged credentials, remote access, and secure connectivity.
• Work on privileged remote access management, privileged remote support, and access governance.
• Migrate and decommission insecure remote access tools (e.g., TeamViewer, Bitvise) and enforce secure alternatives.
• Collaborate with network and infrastructure teams to remove unnecessary firewall rules and strengthen access controls.
• Support IAM & SSO initiatives including RSA, CA SiteMinder, and LDAP directory services.
• Provide troubleshooting and support for PAM and IAM environments, including RSA token authentication and 2FA integrations.
• Document technical configurations, policies, and standard operating procedures.
• Ensure compliance with enterprise security policies, audits, and regulatory requirements.

Required Skills & Qualifications

• 5+ years of experience in Identity & Access Management (IAM) and PAM domains.
• Strong hands-on experience with BeyondTrust Privileged Access Management (Bomgar).
• Knowledge of Single Sign-On (SSO), RSA Authentication, and directory services (LDAP, Oracle Directory, Sun One Directory).
• Experience with CA SiteMinder and web application access management.
• Strong troubleshooting and analytical skills for resolving PAM and IAM issues.

Ability to collaborate with cross-functional teams (security, infrastructure, applications

About NxtWave

NxtWave is one of India’s fastest-growing ed-tech startups, reshaping the tech education landscape by bridging the gap between industry needs and student readiness. With prestigious recognitions such as Technology Pioneer 2024 by the World Economic Forum and Forbes India 30 Under 30, NxtWave’s impact continues to grow rapidly across India.

Our flagship on-campus initiative, NxtWave Institute of Advanced Technologies (NIAT), offers a cutting-edge 4-year Computer Science program designed to groom the next generation of tech leaders, located in Hyderabad’s global tech corridor.

Know more:

🌐 NxtWave | NIAT

About the Role

As a PhD-level Software Development Instructor, you will play a critical role in building India’s most advanced undergraduate tech education ecosystem. You’ll be mentoring bright young minds through a curriculum that fuses rigorous academic principles with real-world software engineering practices. This is a high-impact leadership role that combines teaching, mentorship, research alignment, and curriculum innovation.

Key Responsibilities

• Deliver high-quality classroom instruction in programming, software engineering, and emerging technologies.
• Integrate research-backed pedagogy and industry-relevant practices into classroom delivery.
• Mentor students in academic, career, and project development goals.
• Take ownership of curriculum planning, enhancement, and delivery aligned with academic and industry excellence.
• Drive research-led content development, and contribute to innovation in teaching methodologies.
• Support capstone projects, hackathons, and collaborative research opportunities with industry.
• Foster a high-performance learning environment in classes of 70–100 students.
• Collaborate with cross-functional teams for continuous student development and program quality.
• Actively participate in faculty training, peer reviews, and academic audits.

Eligibility & Requirements

• Ph.D. in Computer Science, IT, or a closely related field from a recognized university.
• Strong academic and research orientation, preferably with publications or project contributions.
• Prior experience in teaching/training/mentoring at the undergraduate/postgraduate level is preferred.
• A deep commitment to education, student success, and continuous improvement.

Must-Have Skills

• Expertise in Python, Java, JavaScript, and advanced programming paradigms.
• Strong foundation in Data Structures, Algorithms, OOP, and Software Engineering principles.
• Excellent communication, classroom delivery, and presentation skills.
• Familiarity with academic content tools like Google Slides, Sheets, Docs.
• Passion for educating, mentoring, and shaping future developers.

Good to Have

• Industry experience or consulting background in software development or research-based roles.
• Proficiency in version control systems (e.g., Git) and agile methodologies.
• Understanding of AI/ML, Cloud Computing, DevOps, Web or Mobile Development.
• A drive to innovate in teaching, curriculum design, and student engagement.

Why Join Us?

• Be at the forefront of shaping India’s tech education revolution.
• Work alongside IIT/IISc alumni, ex-Amazon engineers, and passionate educators.
• Competitive compensation with strong growth potential.
• Create impact at scale by mentoring hundreds of future-ready tech leaders.