Simplify Alpha™
Company:
https://www.linkedin.com/company/simplifyalpha
Industries: IT Services and IT Consulting
Job details:
We are looking for a Senior Data & Integration Engineer to design, build, and support data pipelines, BI reporting, and enterprise integration flows across our health plan technology platform. This role combines hands-on data engineering with AWS Glue, reporting and analytics with Power BI, and integration development with IBM Message Broker / App Connect Enterprise (ACE), and carries a strong expectation of AI-assisted engineering practice. You will be based in Hyderabad in a hybrid work model, partnering closely with onshore architects, business stakeholders, and other engineering teams.
Key Responsibilities
- Design, build, and maintainETL/ELT pipelines using AWS Glue (Python/PySpark) to ingest, transform, andload data across AWS-based data platforms (S3, Redshift, Athena, Glue DataCatalog)
- Develop, publish, and maintaininteractive Power BI dashboards and reports, including data modeling, DAXmeasures, and Power Query (M) transformations
- Design, build, and supportintegration and message flows using IBM Message Broker / App Connect Enterprise(ACE) and IBM MQ for real-time and batch data exchange between internal andexternal systems
- Optimize data pipelines, BIdatasets, and integration flows for performance, reliability, and costefficiency
- Partner with business, data,and platform teams to translate reporting, analytics, and integrationrequirements into technical solutions
- Establish and enforce dataquality, governance, and lineage practices across ETL and integration pipelines
- Troubleshoot and resolveproduction issues across data pipelines, BI datasets, and integration flows,including root-cause analysis and permanent fixes
- Document data flows,integration patterns, and BI semantic models to support internal knowledgesharing
- Mentor junior and mid-levelengineers on data engineering, BI development, and integration best practices
- Collaborate with architects andplatform leads on the evolution of the data and integration architecture
Required Qualifications
- Bachelor's degree in ComputerScience, Engineering, Information Systems, or a related field
- 8–12 years of experience acrossdata engineering, BI development, and/or systems integration, with hands-ondelivery experience in at least two of these areas
- Strong, hands-on experiencewith AWS Glue for ETL/ELT development using Python and/or PySpark
- Working experience withsupporting AWS data services: S3, Redshift, Athena, and Glue Data Catalog
- Strong experience building andadministering Power BI dashboards and reports, including data modeling, DAX,Power Query (M), workspaces, gateways, and scheduled refresh
- Hands-on experience developingand supporting message/integration flows on IBM Message Broker or IBM AppConnect Enterprise (ACE), including ESQL and integration node/serveradministration
- Working knowledge of IBM MQ forqueue and messaging management
- Strong SQL skills acrossrelational databases and cloud data warehouses
- Solid understanding ofdimensional data modeling (star schema) for BI and reporting use cases
- Strong grasp of ETL/ELT designpatterns, data quality checks, and data governance practices
- Strong debugging,performance-tuning, and production-support skills across data pipelines andintegration systems
- Excellent written and verbalcommunication skills for cross-functional and client-facing 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 ETL scripts, Power BI DAX/Power Query logic, and ACE message flows/ESQL
- Able to critically review and validate AI-generated code, transformations, and queries for correctness, performance, and data integrity before deployment
- Practical use of AI tools to assist with data profiling, anomaly detection, dashboard narrative/summary generation, and technical documentation
- Understanding of secure and compliant AI tool usage, including never entering PHI, member data, or other sensitive health plan data into prompts or external AI tools
- Able to identify where AI-driven automation can improve pipeline development, testing, or reporting 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 additional AWS data services: Lambda, Step Functions, EMR, Kinesis, or DMS
- Experience with Kafka or other event-streaming platforms for real-time integration
- Experience with Power BI Premium/Fabric or Power Automate for extended BI automation
- Relevant certifications such as AWS Certified Data Engineer/Analytics Specialty, Microsoft Power BI certifications, or IBM integration certifications
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