Cloud Sara Technologies

Postgress Developer

Experience: 2 to 5 Years

Location: Chennai

Type: Contract

Duration : 6+ Months

Immediate joiners only

Roles & Responsibilities:

Hands-on experience writing efficient SQL queries, views, stored procedures, custom functions, indexing strategies.

Analyse execution plans, and triggers.

Ability to Identify and resolve blocking sessions, deadlock issues, slow queries, and database locks in high-concurrency environments.

PostgreSQL Developer – Chennai

Experience: 2–5 Years

Location: Chennai

Employment Type: Contract

Contract Duration: 6+ Months

Immediate Joiners Only

Payroll: Candidate's existing payroll will continue (Payroll stays with you).

Job Description

We are looking for an experienced PostgreSQL Developer with strong hands-on experience in SQL development, database optimization, and troubleshooting.

Roles & Responsibilities

• Write and optimize efficient SQL queries, views, stored procedures, and custom functions.
• Develop and implement indexing strategies for better database performance.
• Analyze SQL execution plans and optimize query performance.
• Work with database triggers and troubleshoot database-related issues.
• Identify and resolve blocking sessions, deadlocks, slow queries, and database locking issues.
• Handle high-concurrency database environments and ensure optimal performance.

Required Skills

• PostgreSQL
• Advanced SQL
• Stored Procedures & Functions
• Views & Triggers
• Indexing & Query Optimization
• Execution Plan Analysis
• Deadlock & Lock Management
• Performance Tuning

Interested candidates can share their updated resumes.

Databricks BI Developer / Engineer

Rate: 25 LPA

Exp- 5+ years

Location: Remote

Time zone: ET (US Eastern Time)

Shift: Night Shift

Requirements must have: Databricks, Spark, BI (Tableau or something different, or ready to learn quickly)

Task: Main responsibility is the migration of existing Tableau dashboards to Databricks AI/BI Dashboards

We are looking for someone with Databricks experience, strong analytical skills, and the ability to work effectively with ambiguous requirements. Strong communication skills are essential, as the role requires close collaboration with multiple stakeholders, Databricks consultants, and technical teams.

Senior Data Engineer Databricks and Snowflake 

Exp- 7+ years

Rate: 30 LPA

Location: Remote

Time zone: ET (US Eastern time)

Shift: Night Shift

Type: Fulltime

Main tech requirements: Databricks, Snowflake, Spark, AWS, RDS, Oracle, MSSQL, domain of histopathology

Responsibilities:

Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems (e.g., lab systems, MES, clinical supply, quality systems, external partners).

Create and optimize data flows for structured and unstructured data using Python (PySpark), R, SQL, Databricks, Snowflake, and other modern engineering tools.

Develop and maintain specific data repositories, implementing enterprise-level data models, and creating new models as needed.

Enable AI/ML readiness by ensuring data is well-structured, versioned, traceable, and semantically aligned with enterprise data standards.

What we expect:

Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred.

6+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment.

Proficiency with Python, R, SQL, and cloud-based architectures (AWS services, Snowflake, Databricks, Redshift) along with Spark and dbt.

Proficiency in RDS

Expertise in ETL and DWH.

Experience with NoSQL and graph databases.

English language proficiency of B2+

Strong analytical, problem-solving, and stakeholder-management skills, with the ability to translate discussions into actionable requirements.

Ability to drive multiple exciting projects simultaneously with strong organizational skills and adaptability.

Nice to have:

Experience working with the histopathology domain

Experience with regulated or standards-driven data environments, such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards.

Familiarity with high dimensional data (e.g., imaging, sensor data, etc).

Experience with principles connecting to or feeding MLOps and model deployment workflows.

Knowledge of manufacturing systems (MES), laboratory information systems, or industrial data systems.

Exposure to knowledge graph or ontology-driven architectures.

Lead Data Security Solution Engineer

Exp: 10+ years

Rate: 35 LPA

Location: Remote

Time zone: ET (US Eastern time)

Shift: Night Shift

Type: Fulltime​

Responsibilities:

1. Technical and Database Assessment

Review Data In-Licensing requirements, workflow maps, data flows, data lineage, entitlement rules, and dependency records.

Assess relational database platforms, schemas, connectivity methods, interfaces, drivers, service identities, query patterns, and downstream consumption.

Identify where licensed data is stored, transformed, replicated, extracted, cached, archived, or backed up.

Assess current database security capabilities and identify gaps, constraints, risks, and prerequisites.

2. Data-Level Authentication and Identity Integration

Assess authentication for named users, service identities, workloads, and analytical tools accessing databases.

Evaluate OAuth/OIDC or other identity- and token-based authentication directly to the database where supported by the selected technology.

Design integration between enterprise identities, security groups, project groups, database principals, roles, and policy engines.

Reduce reliance on shared or long-lived credentials where feasible and define secure credential or token handling for unavoidable exceptions.

Align with tools currently available and identify gaps if any,

3. Fine-Grained Authorization and Data Firewalling

Design database-level controls that restrict access to explicitly authorized users, groups, services, projects, or licensing populations.

Design and implement row-level security, column-level security, dynamic masking, views, policy-based filtering, or equivalent controls as appropriate.

Define isolation patterns for different licensed datasets and agreements while preserving permitted platform use for other users.

Ensure controls are consistently enforced as close to the data layer as technically feasible and are not solely dependent on application logic.

4. Auditing, Monitoring, and Traceability

Design database auditing to capture who accessed data, what was accessed, when access occurred, and which identity or service was used.

Define logging for queries, exports, failed access attempts, permission changes, and privileged activity where supported and required.

Integrate audit telemetry with appropriate monitoring and reporting capabilities and define retention and evidence requirements.

Validate that audit records are searchable, attributable, protected from inappropriate modification, and useful for investigation.

5. Data Lifecycle, Revocation, and Deletion

Design controls for access revocation when users change roles, leave a project, or when licensing rights expire.

Design methods to identify and remove licensed data from primary stores and relevant downstream copies, extracts, caches, or derived stores.

Address deletion implications for referential integrity, backups, archives, replication, recovery processes, and downstream consumers.

Define validation, exception handling, and evidence mechanisms to demonstrate that required deletion activities were completed.

6. Solution Architecture and Engineering

Translate requirements into current-state and target-state architectures, technical specifications, security patterns, and implementation plans.

Compare solution options and document trade-offs across security, feasibility, performance, scalability, operability, cost, and technology constraints.

Define database connectivity, policy-enforcement, identity, audit, monitoring, lifecycle, and integration components.

Collaborate with database, IAM, security architecture, infrastructure, application, data platform, governance, and scientific teams.

7. POC Design and Execution

Select suitable relational database and workflow candidates that represent Data In-Licensing scenarios and material technical risks.

Define POC architecture, test data, test identities, success criteria, negative tests, performance considerations, and rollback approach.

Implement and validate identity-based authentication, fine-grained authorization, data firewalling, auditing, access revocation, and deletion scenarios.

Document outcomes, limitations, operational considerations, reusable patterns, and recommendations for broader adoption.

What we expect:

Expected Deliverables

Technical assessment of databases, integrations, identities, and data flows

Current-state database security and capability assessment

Target-state data security architecture and detailed technical design

Database authentication and identity-integration design

Row-level, column-level, masking, and policy-enforcement design

Data firewalling and licensed-dataset isolation pattern

Audit, monitoring, traceability, and reporting design

Access revocation, retention, lifecycle, and deletion design

Solution options, feasibility, gap, dependency, and risk assessment

POC architecture, implementation, test results, and recommendations

Reusable implementation patterns and operational handover documentation

Required Technical Skills and Experience

Strong hands-on experience with relational databases, SQL, database architecture, schemas, roles, privileges, and access paths.

Practical experience implementing database-level authorization, including row-level and column-level controls or equivalent fine-grained mechanisms.

Strong knowledge of database authentication, IAM, OAuth 2.0, OIDC, tokens, service identities, workload identities, and secrets management.

Experience designing secure database connectivity and integrations for applications, analytical tools, APIs, ETL/ELT, and data pipelines.

Experience with database auditing, query/activity monitoring, centralized logging, alerting, and investigation support.

Understanding of data lineage, lifecycle, retention, revocation, deletion, backup, archive, and recovery implications.

Ability to evaluate heterogeneous database technologies and design platform-appropriate controls.

Strong architecture, engineering, troubleshooting, documentation, and stakeholder-collaboration skills.

Nice to have:

Experience with enterprise data platforms, cloud or hybrid databases, data catalogs, access governance, and policy-enforcement technologies.

Experience in pharmaceutical research, scientific data, intellectual property protection, data licensing, or another regulated environment.

Experience designing and executing security POCs and converting validated patterns into production-ready designs.

Knowledge of privacy, contractual-use restrictions, segregation, and evidence requirements affecting licensed data.

LEAD DATA SECURITY SOLUTION ENGINEER

Experience: 10+ Years

Location: Remote

Employment Type: Full-Time

Budget: Up to ₹35 LPA

Time Zone: US Eastern Time (ET)

Shift: US ET Night Shift

Job Description

We are looking for an experienced Lead Data Security Solution Engineer with strong expertise in database security, IAM, authentication, authorization, and enterprise data architecture.

The candidate will be responsible for assessing existing database environments, designing secure data access architectures, implementing fine-grained authorization controls, and ensuring licensed data is protected throughout its lifecycle.

The role involves working closely with database, IAM, security, infrastructure, application, data platform, and governance teams.

Key Responsibilities

1. Technical and Database Assessment

• Assess database platforms, schemas, data flows, data lineage, connectivity, and downstream dependencies.
• Review where licensed data is stored, transformed, replicated, extracted, cached, archived, and backed up.
• Evaluate existing database security capabilities and identify gaps, risks, and technical constraints.

2. Authentication and Identity Integration

• Design secure authentication for users, applications, service identities, and workloads.
• Implement or evaluate OAuth 2.0, OIDC, token-based authentication, and enterprise IAM integration.
• Integrate enterprise identities, security groups, database roles, and policy engines.
• Reduce dependency on shared and long-lived credentials.

3. Fine-Grained Authorization and Data Security

• Design and implement database-level access controls.
• Implement Row-Level Security (RLS), Column-Level Security (CLS), dynamic data masking, and policy-based filtering.
• Design secure isolation patterns for licensed datasets.
• Ensure security policies are enforced at the database layer.

4. Auditing, Monitoring, and Traceability

• Design database auditing and activity monitoring.
• Track user access, queries, exports, permission changes, and privileged activities.
• Integrate audit logs with centralized monitoring and reporting systems.
• Define audit retention and investigation requirements.

5. Data Lifecycle and Deletion

• Design access revocation mechanisms for users, projects, and expired licensing agreements.
• Define secure data deletion processes across databases, backups, archives, caches, and downstream systems.
• Ensure deletion activities are validated and supported by audit evidence.

6. Solution Architecture and Engineering

• Develop current-state and target-state security architectures.
• Prepare technical specifications, implementation plans, and reusable security patterns.
• Evaluate solution options based on security, scalability, performance, feasibility, and cost.
• Collaborate with cross-functional technical and business teams.

7. POC Design and Execution

• Design and execute Proof of Concepts (POCs) for database security scenarios.
• Validate authentication, authorization, data isolation, auditing, access revocation, and deletion.
• Document test results, technical limitations, recommendations, and implementation approaches.

Required Technical Skills

• 10+ years of experience in database engineering, data security, solution architecture, or related fields.
• Strong hands-on experience with relational databases, SQL, database architecture, schemas, roles, and privileges.
• Experience implementing Row-Level Security (RLS), Column-Level Security (CLS), dynamic masking, and fine-grained authorization.
• Strong understanding of IAM, OAuth 2.0, OIDC, token-based authentication, service identities, and workload identities.
• Experience with secrets management and secure database connectivity.
• Knowledge of database auditing, query monitoring, centralized logging, alerting, and security investigations.
• Experience securing integrations involving applications, APIs, analytical tools, and ETL/ELT pipelines.
• Understanding of data lineage, retention, lifecycle management, revocation, deletion, backup, and recovery.
• Ability to assess heterogeneous database platforms and recommend suitable security architectures.
• Strong architecture, troubleshooting, documentation, and stakeholder-management skills.

Nice to Have

• Experience with enterprise data platforms and cloud or hybrid database environments.
• Knowledge of data catalogs, access governance, and policy-enforcement technologies.
• Experience in pharmaceutical research, healthcare, scientific data, or intellectual property protection.
• Exposure to data licensing, contractual-use restrictions, and regulated environments.
• Experience designing and executing security POCs and implementing production-ready solutions.

Expected Deliverables

• Database security and capability assessment.
• Current-state and target-state security architecture.
• Database authentication and IAM integration design.
• Fine-grained authorization and data-masking design.
• Data firewalling and licensed-dataset isolation patterns.
• Audit, monitoring, and traceability framework.
• Data revocation, retention, and deletion strategy.
• Technical feasibility, gap, dependency, and risk assessments.
• POC implementation, test results, and recommendations.
• Reusable technical documentation and operational handover.

Work Requirements

• Fully remote opportunity.
• Full-time employment.
• Must be comfortable working in the US Eastern Time (ET) night shift.
• Budget: Up to ₹35 LPA.

SENIOR DATA ENGINEER – DATABRICKS & SNOWFLAKE

Experience: 7+ Years

Location: Remote

Employment Type: Full-Time

Budget: Up to ₹30 LPA

Time Zone: US Eastern Time (ET)

Shift: US ET Night Shift

Job Description

We are looking for an experienced Senior Data Engineer with strong expertise in Databricks, Snowflake, Apache Spark, and AWS to design, develop, and maintain scalable data engineering solutions.

The candidate will work on integrating data from multiple sources, building modern data pipelines, developing enterprise data models, and preparing data platforms for AI/ML applications.

Experience in healthcare, scientific data, or the histopathology domain will be an added advantage.

Key Responsibilities

• Design, build, and maintain scalable data pipelines to acquire, integrate, and manage data from diverse sources such as laboratory systems, MES, clinical supply, quality systems, and external partners.
• Develop and optimize data workflows for structured and unstructured data using Python, PySpark, R, SQL, Databricks, and Snowflake.
• Design and maintain enterprise-level data models and data repositories.
• Perform ETL development, data warehousing, database design, and data integration.
• Ensure data quality, versioning, traceability, and consistency to support AI/ML readiness.
• Collaborate with stakeholders and technical teams to translate business requirements into technical solutions.
• Manage multiple projects while ensuring scalability, performance, and reliability.

Required Skills

• 7+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks and Snowflake.
• Excellent knowledge of Apache Spark / PySpark.
• Strong experience with AWS cloud services and AWS RDS.
• Experience with Oracle and Microsoft SQL Server (MSSQL).
• Proficiency in Python, R, and SQL.
• Strong understanding of ETL, Data Warehousing (DWH), data modeling, and database design.
• Experience with dbt and cloud-based data architectures.
• Knowledge of NoSQL and graph databases.
• Strong analytical, problem-solving, and stakeholder-management skills.
• Good English communication skills (B2 level or above).
• Willingness to work in the US Eastern Time (ET) night shift.

Preferred / Good to Have

• Experience in histopathology, healthcare, life sciences, or scientific data environments.
• Knowledge of CDISC, HL7, FHIR, OMOP, DICOM, or other regulated data standards.
• Experience handling high-dimensional data, including imaging and sensor data.
• Familiarity with MLOps and machine learning model deployment workflows.
• Knowledge of Manufacturing Execution Systems (MES) and Laboratory Information Management Systems (LIMS).
• Exposure to knowledge graphs and ontology-driven architectures.

Education

Bachelor's degree in Engineering, Data Science, Life Sciences, Computer Science, or a related field. A master's degree is preferred.

Interested candidates can apply with their updated resumes.

DAT​​ABRICKS BI DEVELOPER / ENGINEER

Location: Remote

Experience: 5+ Years

Budget: Up to ₹25 LPA

Work Mode: Remote

Shift: US Eastern Time (ET) – Night Shift

Job Description

We are looking for an experienced Databricks BI Developer / Engineer with strong hands-on experience in Databricks and Apache Spark to support a dashboard migration project.

The primary responsibility will be migrating existing Tableau dashboards to Databricks AI/BI Dashboards.

Key Responsibilities

• Migrate existing Tableau dashboards to Databricks AI/BI Dashboards.
• Work with Databricks and Spark to analyse and process data.
• Understand business requirements and translate them into effective BI solutions.
• Collaborate with Databricks consultants, stakeholders, and technical teams.
• Handle ambiguous requirements and provide analytical solutions.
• Ensure dashboard accuracy, performance, and reliability.
• Communicate project progress and technical updates effectively.

Required Skills

• 5+ years of relevant professional experience.
• Strong hands-on experience with Databricks.
• Good experience with Apache Spark / PySpark.
• Experience with Tableau or other BI tools such as Power BI.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management skills.
• Ability to understand and work with evolving or ambiguous requirements.
• Willingness to learn Databricks AI/BI Dashboards quickly, if not already experienced.

Work Requirements

• Remote opportunity.
• Must be comfortable working in the US Eastern Time (ET) night shift.
• Budget: Up to ₹25 LPA.

🚀 We're Hiring – Angular Developer 🚀

📍 Location: Taramani, Chennai

💼 Experience: 1–5 Years

📄 Employment Type: Contract

⏳ Duration: 6+ Months

💰 CTC: ₹2 – ₹3.5 LPA

⚡ Immediate Joiners Only

Skills Required:

✔️ Angular (v12+)

✔️ TypeScript

✔️ JavaScript (ES6+)

✔️ HTML5, CSS3

✔️ SQL

✔️ REST API Integration

✔️ Angular Material / Bootstrap

✔️ Git

🚀 We're Hiring – Node.js Developer 🚀

📍 Location: Taramani, Chennai

💼 Experience: 1–5 Years

📄 Employment Type: Contract

⏳ Duration: 6+ Months

💰 CTC: ₹2 – ₹3.5 LPA

⚡ Immediate Joiners Only

Skills Required:

✔ Node.js

✔ Express.js / NestJS

✔ JavaScript (ES6+)

✔ SQL

✔ REST APIs

✔ JWT/OAuth

✔ MongoDB / PostgreSQL / MySQL

✔ Git