Senior Data Engineer

Simplify Alpha

Hyderabad

On-site

INR 2,500,000 - 4,000,000

Full time

2 days ago
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Job summary

Simplify Alpha is seeking a Senior Data Engineer to design, build, and maintain data pipelines across a health plan technology platform. You will work with AWS-native services and legacy SQL Server/SSIS ETL processes, ensuring reliability and driving modernization alongside multiple engineering teams.

The role emphasizes hands-on development with S3, Redshift, Glue, Athena, Lambda, Step Functions, and ongoing migration of legacy workloads to AWS-native pipelines, while upholding data quality and

Qualifications

  • Bachelor’s degree required in CS/Engineering/Information Systems or related field.
  • 8–12 years of experience in data engineering or ETL development.
  • Hands-on experience with AWS data services: S3, Redshift, Glue, Athena, Lambda, Step Functions.
  • Strong SQL Server skills: T-SQL development, query optimization, performance tuning.
  • Experience building and maintaining SSIS ETL packages.
  • Python scripting for Glue/PySpark ETL development.
  • Dimensional data modeling (star schema).
  • Experience with AWS DMS for migrations.

Responsibilities

  • Design, build, and maintain ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions.
  • Maintain and optimize SQL Server/SSIS ETL workloads and related processes.
  • Write and optimize T-SQL queries, procedures, and views.
  • Support migration of legacy SQL Server/SSIS workloads to AWS-native pipelines.
  • Design and maintain data models supporting analytics and reporting.
  • Use AWS DMS to migrate data from on-premises SQL Server to AWS.
  • Implement data quality checks, validation, and monitoring across pipelines.
  • Optimize pipeline performance, reliability, and cost across AWS and SQL Server workloads.
  • Collaborate with BI, integration, and application teams to ensure data availability.
  • Document data flows and pipeline architectures for knowledge sharing.
  • Troubleshoot production data pipelines and perform root-cause analysis.
  • Mentor junior engineers on data engineering best practices.

Skills

ETL development
Python scripting
Data modeling
SQL performance tuning
AI-assisted development
Data quality and governance
Cross-functional collaboration

Education

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

Tools

AWS
SSIS
Power BI

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 acrossAWS-based data platforms (S3, Redshift, Athena)
  • Maintain, enhance, and troubleshoot existing SQLServer-based ETL processes built in SSIS, including packages, control flows,data flows, and error handling
  • Write and optimize complex T-SQL queries, storedprocedures, and views supporting reporting and downstream applications
  • Support ongoing migration and modernization of legacySQL Server/SSIS ETL workloads to AWS-native data pipelines
  • Design and maintain data models (dimensional/starschema) supporting analytics and reporting use cases
  • Use AWS Database Migration Service (DMS) and relatedtools to support data migration from on-premises SQL Server to AWS
  • Implement data quality checks, validation, andmonitoring across ETL pipelines
  • Optimize pipeline performance, reliability, and costacross 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 applicationlandscape) to ensure data availability and consistency across systems
  • Document data flows, pipeline architecture, and datamodels to support internal knowledge sharing
  • Troubleshoot and resolve production data pipelineissues, including root-cause analysis
  • Mentor junior engineers on data engineering and ETL/ELTbest 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 ETLdevelopment
  • Strong, hands-on experience with AWS data services: S3,Redshift, Glue, Athena, Lambda, and Step Functions
  • Strong, hands-on experience with SQL Server, includingT-SQL development, query optimization, and performance tuning
  • Strong, hands-on experience building and maintainingETL 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 (starschema) 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, andlineage practices
  • Excellent written and verbal communication skills forcross-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 acceleratedevelopment of Glue/PySpark scripts, SSIS package logic, and T-SQL queries
  • Able to critically review and validate AI-generatedcode, queries, and transformations for correctness, performance, and dataintegrity before deployment
  • Practical use of AI tools to assist with dataprofiling, anomaly detection, and technical documentation
  • Understanding of secure and compliant AI tool usage,including never entering PHI, member data, or other sensitive information intoprompts or external AI tools
  • Able to identify where AI-driven automation can improvepipeline development, testing, or migration efficiency, and champion adoptionwithin the team
Preferred Qualifications:
  • Experience in the US health insurance or payer domain:claims, eligibility, enrollment, provider, or member data, with HIPAA-awaredata handling practices
  • Exposure to healthcare data standards (X12 EDI, HL7,FHIR)
  • Experience with Power BI or other BI/reporting toolsconsuming 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 DataEngineer/Analytics Specialty, Microsoft SQL Server certifications
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