Senior Data Engineer

Simplify Alpha; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Simplify Alpha is seeking a Senior Data Engineer to design, build, and maintain data pipelines across health plan technology platforms, leveraging AWS-native services while sustaining SQL Server/SSIS ETL workloads.

You will design scalable data models, perform data migrations to AWS, implement data quality checks, and collaborate with BI teams to ensure reliable data for reporting. Strong Python, SQL, and AWS expertise are essential.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions to ingest, transform, and load data across AWS-based data platforms (S3, Redshift, Athena)
• Maintain, enhance, and troubleshoot existing SQL Server-based ETL processes built in SSIS, including packages, control flows, data flows, and error handling
• Write and optimize complex T-SQL queries, stored procedures, and views supporting reporting and downstream applications
• Support ongoing migration and modernization of legacy SQL Server/SSIS ETL workloads to AWS-native data pipelines
• Design and maintain data models (dimensional/star schema) supporting analytics and reporting use cases
• Use AWS Database Migration Service (DMS) and related tools to support data migration from on-premises SQL Server to AWS
• Implement data quality checks, validation, and monitoring across ETL pipelines
• Optimize pipeline performance, reliability, and cost across both AWS-native and SQL Server/SSIS workloads
• Partner with BI, integration, and application teams (including the Power BI and Edifecs/EDI teams within this application landscape) to ensure data availability and consistency across systems
• Document data flows, pipeline architecture, and data models to support internal knowledge sharing
• Troubleshoot and resolve production data pipeline issues, including root-cause analysis
• Mentor junior engineers on data engineering and ETL/ELT best practices

Skills

AWS data services

SQL Server

Python scripting

Data modeling

ETL development

AI tools usage

Communication skills

Education

Bachelor's degree in Computer Science

Tools

SSIS

Power BI

AWS DMS

AWS Glue

Athena

Lambda

Step Functions

Job description

We are looking for a Senior Data Engineer to design, build, and maintain data pipelines across our health plan technology platform, spanning AWS-native data services and existing SQL Server/SSIS ETL processes. This role sits alongside the other engineering teams in this application landscape (software engineering, Data/BI & Integration, DevOps, and Edifecs EDI), and carries dual responsibility: keeping current SQL Server/SSIS workloads reliable, and helping migrate and modernize them onto AWS-native pipelines.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines using AWSGlue, Lambda, and Step Functions to ingest, transform, and load data across AWS-based data platforms (S3, Redshift, Athena)
• Maintain, enhance, and troubleshoot existing SQL Server-based ETL processes built in SSIS, including packages, control flows, data flows, and error handling
• Write and optimize complex T-SQL queries, stored procedures, and views supporting reporting and downstream applications
• Support ongoing migration and modernization of legacy SQL Server/SSIS ETL workloads to AWS-native data pipelines
• Design and maintain data models (dimensional/star schema) supporting analytics and reporting use cases
• Use AWS Database Migration Service (DMS) and related tools to support data migration from on-premises SQL Server to AWS
• Implement data quality checks, validation, and monitoring across ETL pipelines
• Optimize pipeline performance, reliability, and cost across both AWS-native and SQL Server/SSIS workloads
• Partner with BI, integration, and application teams (including the Power BI and Edifecs/EDI teams within this application landscape) to ensure data availability and consistency across systems
• Document data flows, pipeline architecture, and data models to support internal knowledge sharing
• Troubleshoot and resolve production data pipeline issues, including root-cause analysis
• Mentor junior engineers on data engineering and ETL/ELT best practices

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field
• 8–12 years of experience in data engineering or ETL development
• Strong, hands‑on experience with AWS data services: S3, Redshift, Glue, Athena, Lambda, and Step Functions
• Strong, hands‑on experience with SQL Server, including T‑SQL development, query optimization, and performance tuning
• Strong, hands‑on experience building and maintaining ETL packages in SSIS (control flow, data flow, error handling, and deployment)
• Working proficiency in Python for scripting, automation, and Glue/PySpark‑based ETL development
• Solid understanding of dimensional data modeling (star schema) for analytics and reporting use cases
• Experience with data migration tools and approaches (e.g., AWS DMS) for moving workloads from on-premises SQL Server to AWS
• Strong understanding of data quality, governance, and lineage practices
• 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 development of Glue/PySpark scripts, SSIS package logic, and T‑SQL queries
• Able to critically review and validate AI‑generated code, queries, and transformations for correctness, performance, and data integrity before deployment
• Practical use of AI tools to assist with data profiling, anomaly detection, and technical documentation
• 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 healthcare data standards (X12 EDI, HL7, FHIR)
• Experience with Power BI or other BI/reporting tools consuming the data pipelines you build
• Experience with additional AWS data services: EMR, Kinesis, or Redshift Spectrum
• Experience with modern orchestration tools (e.g., Apache Airflow) as an alternative or complement to SSIS
• Relevant certifications: AWS Certified Data Engineer/Analytics Specialty, Microsoft SQL Server certifications