HIH- Data Management Strategy & Governance Lead Analyst

Advisor, Data Strategy (Cigna Investment Management)

Location: Hyderabad, India (Hybrid)

Reports To: Functionally to Data Enablement Team, Senior Manager, Cigna Investment Manager GCC

Job Family: Finance Data Analytics

The Cigna Investment Management (CIM), Data Enablement Team (DET), is needs to build a data governance model, to build a faster, data-driven investment organization. You will working closely with Investment professionals across the US and India, to turn data and automation opportunities into measurable results.

ABOUT CIGNA INVESTMENT MANAGEMENT

Cigna Investment Management (CIM) has overall responsibility for the over $30 billion of invested assets for Cignas Insurance Portfolios and the Cigna Pension Plans. Cigna is a leading global health services and insurance provider and Fortune 15 company whose invested assets include public and private corporate bonds, commercial mortgages, private corporate mezzanine debt and equity, real estate equity, public equity and short-term investments.

You will execute CIM s Data Strategy. The role requires strong finance and/or investment knowledge, analytical expertise, and the ability to connect business goals to data and technology solutions. This is a business role that works in close partnership with technology teams for implementation and scale.

The Manager in India oversees a blended team of analysts and technical practitioners responsible for building trusted, scalable data assets that power analytics, and process modernization. This role help execute the roadmap, guides architectural direction, ensures quality and governance, and partners with technology teams to transition designs into robust, enterprise-grade production pipelines.

You will demonstrate your skills and capabilities to remove obstacles, and ensure execution of high-quality data products that improve accuracy, speed, and consistency across Finance.

Strategic Leadership

• Define and advance the CIM Data Governance roadmap.
• Identify priorities for data standardization, quality improvement, lineage, KPI harmonization, and reporting modernization.
• Develop the vision for scalable, reusable Investment data assets and semantic models.

End-to-End Delivery Ownership

• Team player responsible for soup-to-nuts delivery, including:
• Deep data profiling and financial data analysis
• Writing SQL/Python transformation logic
• Building prototypes in Fabric, Databricks, Denodo, and BI tools
• Designing data models and standardized, governed data layers
• Performing validation, reconciliation, and documentation
• Creating handoff packages for productionization
• Ensure solutions are designed for long-term maintainability and enterprise scale.

Data Quality, Governance Standards

• Establish and enforce data definitions, lineage, naming conventions, and quality rules.
• Drive structured remediation of data issues and ensure consistent accuracy across domains.
• Promote responsible data use, metadata standards, and documentation practices.

Cross-Functional Partnership

• Collaborate with Technology, Architecture, Engineering, BI, and Governance teams to ensure alignment and scalable implementation.
• Partner with Investment SMEs to understand business needs, validate logic, and confirm accuracy of outputs.
• Integrate data considerations into process reengineering and analytics priorities.

• 5-8 years in Finance/Investment data, analytics engineering, BI, or data strategy.
• Strong SQL expertise and hands-on experience with data transformations.
• Experience designing or building data models, semantic layers, or reporting-ready datasets.
• Understanding of Investment/Finance processes (GL, FPA, cost allocations, forecasting).
• Experience leading teams or delivering complex data programs.
• Familiarity with Fabric, Databricks, Denodo, Power BI preferred.

• Shapes and executes a cohesive Investment data strategy.
• Delivers scalable, trusted data assets that modernize reporting and analytics.
• Drives quality, consistency, and clarity across Finance data.
• Builds a strong technical and strategic capability within the Finance Data Office.

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