Senior Data Engineer

Lead Data Engineer

Level: Senior / Lead

Experience: 9 to 12 years

Location: Pune – Hybrid (2-3 days in office) *** Due to high volume of applicants, only relevant profiles will receive a response - hence please ensure you apply as per the years of exp and skill sets. *** About

Simplify Healthcare : Simplify Healthcare , a

Simplify Group company , is a leading healthcare technology company focused on transforming how U.S. health plans (Payers) operate across benefits, provider, and claims functions. We build cloud-based, AI-driven SaaS platforms that modernize core payer workflows and enable scalable, compliant, and efficient operations.

Our flagship platform, Simplify Health Cloud™ , brings together enterprise-grade solutions for product configuration, benefits administration, provider lifecycle management, claims operations, and experience orchestration. Designed specifically for the U.S. health insurance ecosystem, our platforms are built to support real-world regulatory complexity, operational scale, and continuous change.

Headquartered in Chicago , with a Global Development & Delivery Center in Pune and a global workforce of 900+ professionals, Simplify Healthcare supports more than 70 U.S. health plans. We are a bootstrapped, debt-free organization with over 18 years of profitable growth, combining long-term stability with a strong execution culture. Our work has been consistently recognized by Deloitte (Technology Fast 500™), Inc. (Inc. 5000), FORTUNE, IDC, and Gartner. As we enter our next phase of growth, we continue to invest in applied AI, platform modernization, and leadership talent to shape the future of payer technology. ** Data Engineer experience remains a must-have along with practical, hands-on AI/ML experience.**

Role Summary:

• We are looking for a seasoned Lead Data Engineer to architect and lead the design of scalable, governed, and high-performance data platforms. This role drives technical direction across multi-cloud environments, mentors engineering teams, and ensures data quality, governance, and architectural excellence across the organization.
• Key Responsibilities
• Lead the architecture, design, and delivery of enterprise-scale data platforms across multi-cloud environments.
• Define and enforce ETL/ELT design patterns, dimensional modeling standards, and event-driven architecture practices.
• Establish data governance, access control, and data quality frameworks across teams.
• Drive performance tuning, cost optimization, and technical decision-making for large-scale data systems.
• Mentor engineers, conduct design and code reviews, and set engineering best practices.
• Collaborate with business, analytics, and ML stakeholders to align platform roadmap with strategic goals.

Required & Preferred Skills Must Have:

• AWS / Azure / GCP (at least 2 clouds)
• ETL / ELT design patterns
• Event-driven architecture design
• Dimensional modeling
• Data governance & access control
• Data quality frameworks (Great Expectations, dbt tests)
• Performance Tuning
• Proficient in programming language Python / Scala / Java
• File and Table formats (Parquet, ORC, Avro, Delta, Iceberg, Hudi)

Good to Have:

• Python (pandas, NumPy, scikit-learn)
• LLM / GenAI pipeline orchestration
• Vector databases (Pinecone, Weaviate, pgvector)
• Advanced SQL
• Feature stores (Feast, Tecton)
• ML pipeline tools (MLflow, Kubeflow, SageMaker)