Roles &

- Responsibilities

1. Data Architecture &
- DataMart Development

- Design, develop, and maintain scalable, analytics-ready datasets for enterprise reporting and operational analytics.

- Lead the development and enhancement of enterprise DataMarts, including ODAG, Timeliness, Risk Adjustment, and other healthcare-focused analytical domains.

- Translate business requirements into robust data models, transformations, and reusable analytical datasets.

- Ensure data solutions align with standardized business definitions, data governance principles, and CMS-driven business logic.

- Collaborate with Managed Care, Finance, Operations, and other business stakeholders to understand, stabilize, and operationalize data requirements.

- Perform data profiling, validation, reconciliation, and quality checks to ensure accuracy and consistency.

1. Data Pipeline &
- Data Lake Development

- Design, build, optimize, and maintain scalable ETL/ELT data pipelines.

- Develop data solutions using modern data platforms such as Databricks, Azure Data Lake, Snowflake, or similar technologies.

- Integrate data from multiple enterprise and external sources, including Epic Clarity, Tapestry, healthcare claims, laboratory systems, and external vendors.

- Transform and validate large-scale healthcare datasets, including HEDIS, CMS, claims, lab, enrollment, and provider data.

- Automate recurring data workflows and processes to reduce manual intervention and improve data reliability.

- Monitor pipeline performance, troubleshoot data issues, and implement improvements for scalability and maintainability.

1. Business Intelligence &
- Data Visualization

- Develop and maintain business intelligence dashboards and analytical solutions using Tableau and/or Microsoft Power BI.





- Build dashboards and reporting solutions aligned with enterprise DSS standards, data governance, and visualization best practices.

- Create curated and reusable datasets to enable self-service analytics and reduce dependency on one-off reporting.

- Work closely with business users to translate analytical requirements into meaningful dashboards, KPIs, and actionable insights.

1. AI &
- Advanced Analytics

- Use Python for data transformation, automation, analytical workflows, and advanced data processing.

- Support the integration of AI/ML and Large Language Model (LLM) capabilities into data and analytics solutions.

- Develop or support LLM-based use cases such as data summarization, classification, insight generation, call center analytics, and CRM analytics.

- Partner with data science, technology, and business teams to develop AI-enabled data products that improve operational decision-making.

- Contribute to the transition toward automated, intelligent data pipelines and AI-enriched datasets.

1. Data Quality, Governance &
- Compliance

- Implement data validation, reconciliation, and quality checks across data pipelines and analytical datasets.

- Ensure data solutions are accurate, consistent, traceable, and aligned with enterprise data governance standards.

- Support regulatory, compliance, and audit-driven reporting requirements.

- Work with healthcare data and reporting standards related to CMS, HEDIS, Medicare Advantage, and other regulatory requirements.





Candidate Requirements

- 3+ years of professional experience in Data Analytics, Business Intelligence, Analytics Engineering, or Data Engineering.

- Experience working in a healthcare, managed care, payer, or Epic data environment.

- Strong hands-on experience with SQL, including developing and optimizing complex queries and transformations across large datasets.

- Proven experience designing and developing analytics-ready datasets, dimensional models, and enterprise DataMarts.

- Hands-on experience with modern data platforms such as Databricks, Azure Data Lake, Snowflake, or equivalent.

- Strong experience developing and maintaining ETL/ELT pipelines, including data ingestion, transformation, validation, and automation.

- Experience working with Tableau and/or Microsoft Power BI for dashboard development and data visualization.

- Strong proficiency in Python for data processing, automation, and analytics workflows.

- Experience integrating and transforming data from multiple sources and systems.

- Strong understanding of data quality, data governance, data modeling, and analytics best practices.

Preferred Qualifications

- Experience working with Epic Clarity and/or Tapestry.

- Experience with healthcare datasets such as claims, enrollment, provider, EHR, laboratory, HEDIS, and CMS data.

- Experience supporting CMS, HEDIS, Medicare Advantage, regulatory, or audit-driven reporting.

- Exposure to AI/ML, Generative AI, or LLM-based solutions.

- Experience with LLM use cases such as summarization, classification, natural language processing, and insight generation.

- Experience working with call center, CRM, or operational analytics.

- Robust understanding of healthcare payer/managed care business processes.

📌 Informatica IICS Developer (Hyderabad)
🏢 Datacognit
📍 Hyderabad