About The Role

About Chubb

Chubb is a world leader in insurance. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb employs approximately 40,000 people worldwide. Additional information can be found at: www.chubb.com .

About Chubb India

At Chubb India, we are on an exciting journey of digital transformation driven by a commitment to engineering excellence and analytics. We are proud to share that we have been officially certified as a Great Place to Work® for the third consecutive year, a reflection of the culture at Chubb where we believe in fostering an environment where everyone can thrive, innovate, and grow

With a team of over 2500 talented professionals, we encourage a start-up mindset that promotes collaboration, diverse perspectives, and a solution-driven attitude. We are dedicated to building expertise in engineering, analytics, and automation, empowering our teams to excel in a dynamic digital landscape.

We offer an environment where you will be part of an organization that is dedicated to solving real-world challenges in the insurance industry. Together, we will work to shape the future through innovation and continuous learning.

Position Details

Job Title: Senior Data Analyst
Function/Department: Technology
Location: Hyderabad
Employment Type: Full Time
Reports To: Madhuri Tadepalli

Role Overview

Position Summary

The Data Platform Lead is a senior technical role responsible for owning the design, development, and operational management of the enterprise data platform. The incumbent will lead the end-to-end delivery of data integration pipelines using Azure Data Factory (ADF) and Informatica, manage the cloud data warehouse on Snowflake or Azure Synapse, and drive the enterprise data modeling strategy across all business domains. In addition to the primary platform responsibilities, the role carries a secondary accountability for data stewardship — ensuring data quality standards, governance policies, and data definitions are established and upheld across the data platform in support of reliable and trustworthy data for the organisation.

Requirements

Candidate must possess at least a Bachelor’s Degree in Computer Science, Information Technology, Information Systems, or a related field
Minimum 7 years of working experience in data management, with at least 3 years in a senior or lead capacity covering data platform engineering, data warehousing, or data integration
Hands-on experience with Azure Data Factory (ADF) — designing, building, scheduling, and monitoring data integration pipelines; experience with ADF components including Linked Services, Datasets, Data Flows, Triggers, Integration Runtimes, and pipeline parameterisation
Experience troubleshooting ADF pipeline failures, optimising data flow performance, and implementing error handling and retry logic within ADF pipelines
Hands-on experience with Informatica PowerCenter or Informatica Intelligent Cloud Services (IICS) — designing, developing, and maintaining ETL mappings, workflows, and sessions; ability to build, enhance, and troubleshoot Informatica packages in a production environment
Strong expertise in data warehouse design and management — including dimensional modeling (star/snowflake schema), data vault methodology, and enterprise warehouse operations in production environments
Hands-on experience with cloud data warehouse platforms such as Snowflake, Azure Synapse Analytics, or Azure SQL Data Warehouse, including performance tuning, partitioning strategies, and cost optimisation
Experience with Azure Analysis Services (AAS) for building and managing tabular data models and data cubes to support enterprise BI and self-service analytics
Proven experience in data modeling strategy — developing and maintaining conceptual, logical, and physical data models; proficiency in modeling tools such as ERwin, ER/Studio, or dbt
Strong proficiency in SQL — complex query writing, optimisation, and performance tuning across relational and columnar databases (MSSQL, Snowflake, PostgreSQL)
Familiarity with data governance principles and data stewardship practices — including data quality management, data lineage, metadata management, and data cataloguing (e.g. Microsoft Purview, Collibra, or Alation)
Strong analytical, problem-solving, and conceptual thinking skills with the ability to translate complex business requirements into scalable data platform solutions
Good communication and stakeholder management skills; able to present data platform strategies and findings clearly to both technical and non-technical audiences
Exposure to Business Intelligence (BI) and reporting tools such as Power BI and SQL SSRS will be an added advantage
Experience with scripting languages such as Python or PowerShell for data automation and pipeline orchestration will be an added advantage
Familiarity with regulatory and compliance requirements relevant to data management (e.g. GDPR, data residency policies) will be an added advantage

Responsibilities

Azure Data Factory (ADF) Pipeline Management

Design, build, and maintain ADF pipelines to support data ingestion, transformation, and distribution across source systems, the data warehouse, and downstream consumers
Configure and manage ADF components including Linked Services, Datasets, Mapping Data Flows, Copy Activities, Triggers, and Self-hosted Integration Runtimes to meet enterprise data integration requirements
Implement parameterised and reusable pipeline patterns to standardise data movement across projects, reducing duplication and improving maintainability
Monitor ADF pipeline runs, proactively detect and resolve failures, and implement robust error handling, alerting, and retry strategies to ensure pipeline reliability and SLA adherence
Optimise ADF Data Flow performance through partition tuning, compute scaling, and transformation logic review to reduce execution times and Azure compute costs
Govern ADF development standards — naming conventions, version control via Git integration, and deployment practices across DEV, SIT, UAT, and PROD environments

Informatica ETL Development

Design, develop, and maintain Informatica PowerCenter or IICS ETL mappings and workflows to support data integration between source systems and the data warehouse
Troubleshoot Informatica mapping failures, session logs, and data quality issues in production; perform root cause analysis and apply fixes within agreed SLAs
Evaluate and recommend the appropriate integration tool (ADF vs Informatica) for each use case based on data volume, transformation complexity, latency requirements, and cost considerations

Data Warehouse Management

Own the design, management, and continuous optimisation of the enterprise data warehouse — including schema design, partitioning strategies, indexing, clustering, and storage cost management on cloud platforms (Snowflake, Azure Synapse)
Define and govern warehouse architecture standards — naming conventions, layering strategy (raw, curated, consumption), access control patterns, and change management processes
Monitor warehouse performance, capacity, and usage; implement tuning measures and apply platform upgrades or patches as required
Collaborate with ETL and data engineering teams to ensure data pipelines deliver clean, well-structured, and performant data into the warehouse layers in accordance with agreed SLAs

Azure Analysis Services (Data Cube)

Design, build, and maintain AAS tabular models to serve as the semantic layer for enterprise BI and self-service analytics
Define measures, KPIs, calculated columns, hierarchies, and perspectives within AAS models to meet business reporting requirements
Manage AAS model deployment, partitioning strategies, and incremental refresh schedules to ensure timely and cost-efficient data cube processing
Optimise AAS query performance through DAX tuning, aggregation design, and partition management; govern data cube access control through row-level security (RLS) and role-based permissions

Data Modeling Strategy

Lead the enterprise data modeling strategy — defining standards, tooling, and review processes for conceptual, logical, and physical data models across all business domains
Design and maintain authoritative canonical data models serving as the single source of truth for key business entities (e.g. policy, claim, customer, premium)
Review and approve data model changes, ensuring alignment with enterprise standards, normalisation principles, and downstream consumption needs
Drive adoption of dimensional modeling (star/snowflake schema) and/or data vault patterns, advising teams on the right modeling approach for their use case
Partner with solution architects, data engineers, and business analysts to embed data modeling into the project delivery lifecycle from inception through to production

Data Stewardship (Secondary Accountability)

In addition to the primary platform responsibilities, the Data Platform Lead is expected to support and uphold data governance and stewardship practices within the data platform domain.

Enforce data definitions, data quality standards, and data access policies for data assets within the platform, working in collaboration with business data owners and the data governance team
Maintain data lineage documentation and metadata for pipelines, warehouse layers, and AAS models to ensure data assets are traceable, discoverable, and well-understood by consumers
Monitor data quality within the platform; identify and escalate data quality issues to the relevant data owners, and implement corrective measures at the pipeline or model level
Adhere to and enforce data change management, data security standards, and governance best practices across all data platform deliverables

General

Create and maintain technical documentation including pipeline design, data model specifications, warehouse architecture standards, and AAS model documentation
Coordinate with IT infrastructure, application development, and business teams to support data platform reliability and continuous improvement
Participate in new projects and major system enhancements to ensure data platform, ADF integration, and warehouse designs align with enterprise best practices

Why Join Us?

Be at the forefront of digital transformation in the insurance industry.
Lead impactful initiatives that simplify claims processing and enhance customer satisfaction.
Work alongside experienced professionals in a collaborative, innovation-driven environment.

Why Chubb?
Join Chubb to be part of a leading global insurance company!
Our constant focus on employee experience along with a start-up-like culture empowers you to achieve impactful results.

Industry leader: Chubb is a world leader in the insurance industry, powered by underwriting and engineering excellence
A Great Place to work: Chubb India has been recognized as a Great Place to Work® for the years 2023-2024, 2024-2025 and 2025-2026
Laser focus on excellence : At Chubb we pride ourselves on our culture of greatness where excellence is a mindset and a way of being. We constantly seek new and innovative ways to excel at work and deliver outstanding results
Start-Up Culture : Embracing the spirit of a start-up, our focus on speed and agility enables us to respond swiftly to market requirements, while a culture of ownership empowers employees to drive results that matter
Growth and success : As we continue to grow, we are steadfast in our commitment to provide our employees with the best work experience, enabling them to advance their careers in a conducive environment

Employee Benefits

Our company offers a comprehensive benefits package designed to support our employees’ health, well-being, and professional growth. Employees enjoy flexible work options, generous paid time off, and robust health coverage, including treatment for dental and vision related requirements. We invest in the future of our employees through continuous learning opportunities and career advancement programs, while fostering a supportive and inclusive work environment. Our benefits include:

Savings and Investment plans: We provide specialized benefits like Corporate NPS (National Pension Scheme), Employee Stock Purchase Plan (ESPP), Long-Term Incentive Plan (LTIP), Retiral Benefits and Car Lease that help employees optimally plan their finances
Upskilling and career growth opportunities: With a focus on continuous learning, we offer customized programs that support upskilling like Education Reimbursement Programs, Certification programs and access to global learning programs.
Health and Welfare Benefits: We care about our employees’ well-being in and out of work and have benefits like Hybrid Work Environment, Employee Assistance Program (EAP), Yearly Free Health campaigns and comprehensive Insurance benefits.

Application Process

Our recruitment process is designed to be transparent, and inclusive.

Step 1 : Submit your application via the Chubb Careers Portal.
Step 2 : Engage with our recruitment team for an initial discussion.
Step 3 : Participate in HackerRank assessments/technical/functional interviews and assessments (if applicable).
Step 4 : Final interaction with Chubb leadership.

Join Us

With you Chubb is better. Whether you are solving challenges on a global stage or creating innovative solutions for local markets, your contributions will help shape the future. If you value integrity, innovation, and inclusion , and are ready to make a difference, we invite you to be part of Chubb India’s journey .

Apply Now : https://www.chubb.com/emea-careers/