Quantiphi

We're looking for a Senior Data Modeler to lead the design and evolution of our enterprise data warehouse, with a primary focus on transforming Guidewire (PolicyCenter, BillingCenter, ClaimCenter) and other insurance source system data into well-architected, analytics-ready models on Google BigQuery. This is a hands-on, high-autonomy role for someone who can own modeling decisions end-to-end — from source system analysis through to production-grade dimensional or Data Vault structures — with minimal oversight.

You'll work across multiple insurance lines of business (Property, Casualty, Financial Lines, Specialty) and partner closely with engineering, BI, and business stakeholders to ensure the data model is technically sound and supports reporting, actuarial, and analytics use cases.

Responsibilities:

• Design and own enterprise-scale data models across multiple insurance domains.
• Translate complex Guidewire schemas (PolicyCenter, BillingCenter, ClaimCenter) into governed warehouse structures.
• Apply appropriate modeling techniques including:
• Dimensional Modeling (Star/Snowflake)
• 3NF/Normalized Modeling
• Data Vault 2.0 (Hubs, Links, Satellites)
• Hybrid and Denormalized Models
• Model effective-dated and slowly changing insurance data, including policy versioning, endorsements, premium earning, and claims history.
• Design conformed dimensions and fact tables supporting Premium, Claims, and Billing reporting.
• Optimize BigQuery performance through partitioning, clustering, materialized views, query tuning, and cost-efficient schema design.
• Create and maintain ERDs, source-to-target mappings, data dictionaries, and lineage documentation.
• Collaborate with Data Engineers to ensure physical implementation aligns with logical models.
• Establish modeling standards and mentor team members through hands-on leadership.
• Independently drive solutions from ambiguous business requirements.
• Communicate modeling decisions and trade-offs to both technical and business stakeholders.

Required Skills & Experience:

• 7+ years of enterprise-scale Data Modeling experience.
• Strong Insurance domain expertise, preferably with Guidewire:
• PolicyCenter
• BillingCenter
• ClaimCenter
• Experience with alternative insurance platforms such as Duck Creek or Sapiens is also valuable.
• Deep expertise in:
• Dimensional Modeling (Kimball)
• 3NF Data Modeling
• Data Vault 2.0
• Denormalized Data Warehousing
• Strong BigQuery knowledge:
• Partitioning & Clustering
• Query Performance Optimization
• Cost-Aware Schema Design
• Expertise in modeling effective-dated and temporal data.
• Excellent communication and stakeholder management skills.
• Proven ability to lead through hands-on technical contributions.
• Ability to work independently with minimal supervision.

Nice to Have:

• Insurance premium calculations and reconciliation:
• Earned / Unearned / Written Premium
• GWP Reconciliation
• Premium Earning Schedules
• Knowledge of Guidewire data model patterns:
• Effective Dating
• FixedID / BranchID
• CDA / ODS Layers
• Experience with Data Vault automation tools.
• Exposure to Snowflake or Redshift.
• Experience mentoring Data Modelers and Data Engineers.

What Success Looks Like:

• Well-documented, scalable enterprise data models.
• Cost-efficient, high-performance modeling decisions.
• Improved modeling maturity across the team.
• Strong stakeholder confidence in the data architecture and design decisions.

We are looking for an experienced BI Solution Architect to lead the design and implementation of scalable, secure, and high-performing Data & BI platforms across Azure and GCP environments.

This role will own the end-to-end data architecture covering ingestion, storage, processing, transformation, analytics, and visualization while driving enterprise BI strategy, reporting governance, and modernization initiatives. The ideal candidate will work closely with business stakeholders, enterprise architects, and engineering teams to deliver robust, production-ready analytics solutions.

Key Responsibilities:

Data Architecture & Solution Design

• Define architecture for data ingestion, storage, processing, and transformation across Azure and GCP.
• Design scalable, resilient, and enterprise-grade data platforms aligned with architectural standards.
• Create data models, architecture blueprints, and end-to-end data flow designs.
• Collaborate with enterprise architects to ensure architectural compliance and governance.

Data Platform & Pipeline Architecture

• Design and oversee large-scale distributed data platforms and pipelines.
• Define standards for data ingestion, transformation, and consumption layers.
• Enable development of scalable and reusable data products.
• Promote modern data architectures including:
• Data Lake
• Lakehouse
• Data Mesh

BI Strategy & Architecture

• Define and drive enterprise BI strategy aligned with business objectives.
• Standardize BI architecture and reporting frameworks across the organization.
• Evaluate and recommend BI technologies including:
• Power BI
• Tableau
• SAP Business Objects (BO)
• Develop reusable blueprints, patterns, and accelerators.
• Lead proof-of-concepts (POCs) and BI modernization initiatives.

Visualization Governance

• Establish dashboard development standards and visualization best practices.
• Define governance frameworks to improve dashboard quality, consistency, and usability.
• Review dashboards prior to production deployment.
• Guide teams in creating intuitive, business-focused, and high-performance visualizations.

Data Governance & Enterprise Data Management

• Define and enforce enterprise data governance standards.
• Drive metadata management, master data management, and reference data practices.
• Establish data quality frameworks, validation mechanisms, and monitoring processes.
• Create technical glossaries and enterprise-wide data standards.

Security & Compliance

• Define access management and security standards across Data & BI platforms.
• Implement controls for sensitive and regulated data.
• Ensure compliance with enterprise policies and regulatory requirements.

Performance & Optimization

• Define monitoring, tuning, and optimization strategies for data pipelines and dashboards.
• Ensure scalability, responsiveness, and reliability of analytics platforms.
• Implement proactive monitoring and observability frameworks.

Leadership & Stakeholder Management

• Partner with Product Owners, Business Analysts, and stakeholders to translate requirements into architecture solutions.
• Collaborate with Data Engineers, Analysts, and Data Scientists to solve complex technical challenges.
• Mentor engineers and associate architects.
• Lead architecture reviews and drive solution governance.

Data Lifecycle & Operations

• Own end-to-end data lifecycle management:
• Ingestion
• Processing
• Storage
• Archival
• Ensure operational readiness and reliability of critical data platforms.
• Drive best practices around scalability, resilience, and sustainability.

Migration & Modernization

• Lead Tableau-to-Power BI migration strategy and execution.
• Design dual-platform architectures to ensure business continuity during migration.
• Drive legacy platform rationalization and modernization initiatives.
• Optimize infrastructure and licensing costs while reducing total cost of ownership (TCO).

Required Qualifications

Experience

• 8+ years of experience in Data Engineering, Big Data, Analytics, or Data Architecture.
• Proven experience designing enterprise-scale data platforms and analytics solutions.
• Strong stakeholder management and leadership experience.

Technical Expertise

• Strong expertise in Azure and GCP data ecosystems.
• Deep understanding of:
• Data Modeling
• ETL / ELT
• Distributed Systems
• Enterprise Data Platforms
• Experience with modern architectures:
• Data Lake
• Lakehouse
• Data Mesh

BI & Analytics

• Strong hands-on experience with:
• Power BI
• Tableau
• SAP Business Objects (BO)
• Expertise in:
• BI Architecture
• Dashboard Design
• Visualization Best Practices
• Reporting Governance

Data Governance

• Strong understanding of:
• Data Governance
• Data Quality
• Metadata Management
• Data Lifecycle Management

Must-Have Skills

• Data Architecture & Solution Design (Azure & GCP)
• Large-Scale Data Platform & Pipeline Design
• Data Modeling & ETL/ELT Architecture
• Distributed Systems
• Data Lake / Lakehouse / Data Mesh
• Power BI & Tableau
• Data Governance & Data Quality
• Enterprise BI Architecture
• Stakeholder Management & Leadership

Good-to-Have Skills

• Enterprise Data Platforms & Multi-Cloud Environments
• CI/CD Pipelines & Automation for Data & BI Platforms
• Real-Time / Streaming Data Architectures
• BI Transformation & Modernization Programs
• Tableau to Power BI Migration Experience
• Azure Data Engineer / Architect Certifications
• GCP Professional Data Engineer / Cloud Architect Certifications

Why Join Us?

• Lead architecture for enterprise-scale Data & BI platforms.
• Drive organization-wide data and analytics strategy.
• Work on modern cloud ecosystems across Azure and GCP.
• High ownership, visibility, and stakeholder exposure.
• Opportunity to shape long-term data, analytics, and visualization roadmaps.

Key Responsibilities

1. Target State Design

• Design and implement a scalable, secure, and domain-driven Data Lakehouse architecture on GCP.
• Define enterprise-grade data architecture standards and reference frameworks.

2. Migration Leadership

• Lead end-to-end migration from legacy platforms (Exasol, Lua, Control-M) to GCP BigQuery and Dataform.
• Drive migration planning, execution, validation, and optimization.

3. Data Modeling

• Design conceptual, logical, and physical data models.
• Implement:
• Data Vault 2.0 (Silver Layer)
• Dimensional Modeling (Gold Layer)

4. Framework Development

• Build reusable, configuration-driven data pipeline frameworks.
• Establish best practices for scalable and accelerated development.

5. Governance & Security

• Implement enterprise data governance using:
• Dataplex
• Data Catalog
• Analytics Hub
• Enable data lineage, cataloging, automated data quality checks, and PII masking using DLP.

6. Orchestration & Automation

• Architect workflows using Cloud Composer (Airflow).
• Automate infrastructure provisioning through Terraform (IaC).

7. BI Modernization

• Reconfigure and validate:
• ~1,000 Tableau & Power BI dashboards
• ~250 semantic/data models
• Ensure successful migration to BigQuery curated layers.

8. Stakeholder Management

• Partner with Engineering Leads, Architects, and Business Teams.
• Translate business requirements into Technical Design Documents (TDDs).
• Drive architecture reviews and approvals.

9. Quality Assurance

• Conduct code reviews and enforce enterprise standards.
• Support UAT and automated validation using QuerySurge.

10. Team Leadership

• Mentor data engineering teams.
• Conduct technical enablement sessions and knowledge transfer workshops.

Required Skills & Experience

Data Engineering & Database Expertise

• Strong expertise in BigQuery architecture, optimization, and stored procedures.
• Advanced SQL programming skills.
• Experience modernizing legacy ETL (Lua-based) into modern ELT frameworks.
• Strong understanding of:
• Data Vault 2.0
• Dimensional Modeling
• Experience with Exasol or similar legacy data warehouses is highly preferred.

GCP & Modern Data Stack

• Hands-on experience with:
• BigQuery
• Dataform (Mandatory)
• Cloud Composer (Airflow)
• Dataflow
• GCS
• Deep expertise in:
• Dataplex
• Data Catalog
• Analytics Hub

Security & Governance

• Experience implementing:
• IAM Roles & Policies
• Cloud KMS
• DLP API
• Strong understanding of enterprise governance and compliance frameworks.

Architecture & DevOps

• Enterprise Data Architecture design experience.
• Cost estimation, sizing, and capacity planning on GCP.
• CI/CD implementation and Terraform-based infrastructure automation.

Soft Skills

• Strong stakeholder management and communication skills.
• Experience leading discovery and solution design workshops.
• Ability to lead distributed Agile/Scrum teams.
• Excellent technical documentation skills (TDD/TSD creation).

Must-Have Skills

• 10+ years of Data Engineering / Data Architecture experience.
• Expertise in GCP BigQuery and Dataform.
• Hands-on experience with Data Vault 2.0.
• Experience implementing Dataplex for governance and security.
• Strong Terraform expertise.
• Proven experience migrating legacy warehouses such as:
• Exasol
• Teradata
• Netezza
• Similar enterprise DW platforms

Good-to-Have Skills

• Lua scripting experience.
• Control-M orchestration experience.
• Tableau and Power BI semantic/data model migration.
• QuerySurge for automated data validation.
• GCP Professional Data Engineer or Professional Cloud Architect certification.

Ideal Candidate Profile

• 10–15+ years of Data Engineering/Data Architecture experience.
• Led large-scale cloud modernization programs.
• Strong expertise in GCP Lakehouse architecture, governance, and migration frameworks.
• Comfortable working with enterprise stakeholders and leading cross-functional migration initiatives.

As a Senior Software Developer at Quantiphi, you will be responsible for designing, developing, and modernizing enterprise-grade applications using the Microsoft .NET ecosystem. You will work closely with stakeholders to gather requirements, build scalable and secure solutions, lead cloud migration initiatives, and mentor engineering teams while ensuring high standards of software quality and performance.

Key Responsibilities

Application Development & Architecture

• Design, develop, and maintain enterprise applications using C#, .NET Core, and ASP.NET Core.
• Build and maintain RESTful APIs using ASP.NET Core.
• Implement scalable, maintainable, and testable solutions following:
• Clean Architecture
• Hexagonal Architecture
• Domain-Driven Design (DDD)
• Apply design patterns including:
• Repository Pattern
• Factory Pattern
• Strategy Pattern
• CQRS
• Dependency Injection

Modernization & Cloud Migration

• Lead application modernization initiatives from on-premises environments to cloud platforms.
• Assess legacy .NET Framework applications and define migration strategies to .NET 6 / .NET 8.
• Transform monolithic applications into modular or microservices-based architectures.
• Conduct application discovery, dependency analysis, and proof-of-concept (POC) activities.
• Create migration roadmaps, rollback plans, and risk mitigation strategies.

Cloud & Containerization

• Design, deploy, and manage applications on AWS Cloud.
• Develop containerized solutions using Docker and Kubernetes.
• Build and maintain automated CI/CD pipelines.
• Implement cloud-native deployment and infrastructure automation practices.

Performance & Scalability

• Design highly scalable systems capable of handling millions of requests and high transaction volumes.
• Optimize application performance through:
• Caching
• Connection Pooling
• Asynchronous Processing
• Database Optimization
• Identify and resolve performance bottlenecks across application, database, and infrastructure layers.
• Implement distributed caching and scalable architectural patterns.

Security & Identity Management

• Implement authentication and authorization using:
• JWT
• OAuth2
• OpenID Connect
• Apply security best practices including:
• HTTPS
• Secure Headers
• Secret Management
• Input Validation
• Ensure compliance with enterprise security and governance standards.

DevOps & Observability

• Establish comprehensive testing strategies:
• Unit Testing
• Integration Testing
• Contract Testing
• End-to-End Testing
• Build and maintain CI/CD pipelines using GitHub Actions, Jenkins, or similar tools.
• Implement monitoring, logging, distributed tracing, and alerting solutions.
• Ensure application reliability, availability, and operational excellence.

Leadership & Collaboration

• Mentor and guide junior and mid-level developers.
• Drive technical decisions and architecture reviews.
• Collaborate with product owners, architects, business stakeholders, and engineering teams.
• Manage technical debt and promote engineering best practices.

Required Technical Skills

Languages & Frameworks

• C#
• .NET Framework 4.x
• .NET 6 / .NET 8
• ASP.NET MVC
• ASP.NET Core MVC

Data Technologies

• SQL Server
• Entity Framework Core
• LINQ
• ADO.NET

Cloud & DevOps

• AWS:
• EC2
• S3
• RDS
• DynamoDB
• ECS
• EKS
• Lambda
• IAM
• VPC
• CloudFormation
• CDK.NET
• AWS SDK for .NET
• Docker
• Kubernetes
• GitHub Actions
• Jenkins
• CI/CD Pipelines

Security

• JWT
• OAuth2
• OpenID Connect
• Identity Providers (IdPs)

Architecture & Design

• Clean Architecture
• Hexagonal Architecture
• CQRS
• Microservices
• Domain-Driven Design (DDD)
• Event-Driven Architecture

Preferred Experience

• 8+ years of software development experience.
• Hands-on experience in cloud migration and modernization projects.
• Experience building enterprise-scale distributed systems and microservices.
• Strong understanding of software architecture, security, and DevOps practices.
• Proven experience leading technical initiatives and mentoring development teams.

We are looking for a hands-on Associate / Architect – Generative AI to design, build, and deploy enterprise-grade GenAI platform capabilities across multiple business units. This role focuses on developing scalable and reusable AI components across the full stack, covering RAG systems, agent orchestration, LLM infrastructure, and GenAIOps on GCP (primary) and Azure.

Key Responsibilities

• Design and build production-ready Generative AI systems and platform components
• Develop and deploy scalable RAG pipelines including data ingestion, embeddings, retrieval, and APIs
• Build agentic AI systems with orchestration, routing, memory, and workflow management
• Develop and manage LLM infrastructure including model routing, caching, observability, and rate limiting
• Build scalable backend services and APIs for AI-driven applications
• Implement GenAIOps/MLOps practices including prompt management, evaluation, monitoring, and deployment
• Work extensively with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, and Pub/Sub
• Ensure AI governance, safety, compliance, PII protection, and auditability standards are maintained
• Design scalable enterprise AI architectures with strong focus on performance, reliability, and reusability
• Collaborate with cross-functional teams to deliver enterprise-grade AI solutions
• Mentor junior engineers and contribute to technical leadership, architecture discussions, and design reviews

Required Skills & Experience

• Strong hands-on experience building and deploying production-grade Generative AI and RAG systems
• Experience working on multi-agent or agentic AI architectures
• Strong proficiency in Python and backend/API development
• Hands-on experience with GCP AI/ML ecosystem including Vertex AI and BigQuery
• Solid understanding of LLM infrastructure, orchestration layers, and AI platform engineering
• Experience with CI/CD pipelines and Infrastructure as Code tools like Terraform
• Good understanding of GenAIOps/MLOps practices and model lifecycle management
• Strong system design and architecture experience for scalable AI platforms
• Exposure to enterprise application architecture and distributed systems
• Experience leading small engineering teams, mentoring developers, or owning technical delivery is preferred
• Understanding of AI safety, governance, and compliance best practices

Nice to Have

• Experience with LangChain, LlamaIndex, or similar frameworks
• Familiarity with RAG evaluation tools such as RAGAS or DeepEval
• Knowledge of Knowledge Graphs with RAG systems
• Experience working in multi-cloud environments (GCP + Azure)
• Exposure to BFSI or other regulated domains

What We’re Looking For

• Engineers who have built and deployed real-world GenAI systems at scale
• Strong backend engineering and systems-thinking mindset
• Ability to thrive in fast-paced enterprise environments
• Ownership mindset with strong communication and collaboration skills 

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Some company highlights:

• Quantiphi has seen 2.5x growth YoY since its inception in 2013.
• Winner of the "Machine Learning Partner of the Year" award from Google for two consecutive years - 2017 and 2018.
• Winner of the "Social Impact Partner of the Year" award from Google for 2019.
• Headquartered in Boston, with 700+ data science professionals across different offices.

For more details, visit: our http://www.quantiphi.com/">Website or our https://www.linkedin.com/company/quantiphi/">LinkedIn Page

Job Description

Role:                                 Associate Tech Architect / Tech Architect – ReactJS +Python+AWS

Experience Level:           7-13 Years

Work location:                Mumbai & Bangalore

We are looking for an experienced full stack developer( ReactJS and Python ) who can help create dynamic software applications for our clients with their skill set. In this role, you will be responsible for gathering requirements from clients and accordingly write and test scalable code, and develop front end and back-end components.

Technologies worked on:

ReactJS, Python, AWS

Requirement Description:

• Full Stack developer with experience in ReactJS, Python, API Gateway, Fargate and ECS
• Well-experienced in working with tools like Git, Maven, JFrog
• Should have a solid understanding of object-oriented programming (OOP)
• Well-experienced to perform Unit Testing and Integration Testing and have good experience in Agile based development approach
• Expertise in developing enterprise-level web applications and REST and SOAP APIs using MicroServices, with demonstrable production-scale experience
• Demonstrate strong design and programming skills using JSON, Web Services, XML, XSLT, PL/SQL in Unix and Windows environments
• Strong background working with Linux/UNIX environments and strong Shell scripting experience
• Working knowledge with SQL or  No SQL databases
• Understand Architecture Requirements and ensure effective design, development, validation, and support activities
• Understanding of core AWS services, uses, and basic AWS architecture best practices
• Proficiency in developing, deploying, and debugging cloud-based applications using AWS
• Ability to use the AWS service APIs, AWS CLI, and SDKs to write applications
• Ability to identify key features of AWS services
• Identify bottlenecks and bugs, and recommend solutions by comparing the advantages and disadvantages of custom development
• Should contribute to team meetings, troubleshooting development and production problems across multiple environments and operating platforms
• Execute strong collaboration and communication skills within distributed project teams
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency