TI
Technical Lead- Data Engineer
Tranzeal Inc.
🇮🇳 India
Hybrid
Staff / Principal
1 week ago
- Apache Spark
- AWS Glue
- Athena
- Power BI
- SQL
- AI
- Devops
- EDI
- AWS
- ETL
- ELT
- PySpark
- DAX
- Power Query
- Data Modeling
- Claude Code
- Cursor
- HIPAA
- X12
- HL7
- FHIR
- Redshift
- EMR
- Health insurance
1 week ago
Location: Hyderabad, India (Hybrid - 3 Days WFO)
Experience: 8–10 years
CTC : 30.7 LPA
Notice period : Immediate to 30Days Max
Tech Stack: Apache Spark (batch and streaming), AWS Glue, S3, Athena, Power BI, SQL, AI-Assisted Development
Role Overview
We are looking for a Tech Lead to build and run the data and reporting layer of our health plan technology platform — batch and streaming pipelines on AWS Glue and Spark, and the Power BI models and reports built on top of them. The role sits within the Data/BI & Integration team alongside software engineering, DevOps and Edifecs EDI, and consumes event and file feeds from the platform's integration layer as well as core AWS sources. The Tech Lead sets the engineering standards for this team and is the offshore technical point of contact for the onshore Data & BI manager.
Key Responsibilities
• Set the patterns and standards for Glue jobs, Spark code, and Power BI models
• Review code and Power BI models produced by the team, and mentor senior and mid-level engineers
• Break down and estimate work, and act as the offshore technical point of contact for the onshore Data & BI manager and partner teams (integration, Edifecs/EDI, application)
• Design, build, and maintain batch ETL/ELT pipelines using AWS Glue and PySpark across S3 and Athena
• Build and maintain streaming pipelines in Spark for near-real-time ingestion of claims, eligibility, and enrollment events
• Own the Glue Data Catalog — crawlers, table definitions, job orchestration, and scheduling
• Build and maintain Power BI semantic models and reports — star-schema datasets, DAX measures, and Power Query transformations
• Write and optimize SQL supporting pipelines, reporting datasets, and downstream applications
• Design and maintain dimensional data models (star schema) supporting analytics and reporting use cases
• Implement data quality checks, validation, and monitoring across both batch and streaming pipelines
• Troubleshoot and resolve production issues across Glue jobs, streaming jobs, and Power BI datasets, including root-cause analysis
• Document data flows, pipeline architecture, and data models to support internal knowledge sharing
Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field
• 8–10 years of experience in data engineering or ETL development
• Strong, hands-on experience with Apache Spark (PySpark) — transformations, joins, and aggregations at scale
• Strong, hands-on experience with AWS Glue: jobs, crawlers, the Data Catalog, and the surrounding S3 and Athena stack
• Hands-on experience with Spark streaming in production
• Strong, hands-on experience with Power BI: data modeling, DAX, and Power Query
• Strong SQL, including query optimization against large datasets
• Solid understanding of dimensional data modeling (star schema) for analytics and reporting use cases
• Strong debugging and production-support skills across data pipelines
• Experience leading a small engineering team or owning a workstream end to end, including design ownership and review
• Track record of design decisions and trade-offs on AWS data platforms, with the reasoning to defend them
• Excellent written and verbal communication skills for cross-functional collaboration
AI Knowledge & AI-Assisted Development (Required)
• Daily, practical use of AI coding/assistant tools (e.g., Claude Code, GitHub Copilot, Cursor, or similar) to accelerate PySpark, SQL, and DAX development
• Able to critically review and validate AI-generated code, queries, and transformations for correctness, performance, and data integrity before deployment
• Understanding of secure and compliant AI tool usage, including never entering PHI, member data, or other sensitive information into prompts or external AI tools
• Able to identify where AI-driven automation can improve pipeline development, testing, or migration efficiency, and champion adoption within the team
Preferred Qualifications
• Experience in the US health insurance or payer domain: claims, eligibility, enrollment, provider, or member data, with HIPAA-aware data handling practices
• Exposure to IBM App Connect Enterprise (ACE), IBM Integration Bus / Message Broker, or IBM MQ as an upstream source of event and file feeds
• Exposure to healthcare data standards (X12 EDI, HL7, FHIR)
• Experience with additional AWS data services: Redshift, Redshift Spectrum, or EMR
• Relevant certifications: AWS Certified Data Engineer, or Microsoft PL-300 (Power BI Data Analyst)
Technical Lead- Data Engineer · Tranzeal Inc.