Senior Data Engineer

Location

Bangalore/Hyderabad

Experience

5+ Years Data Engineering | Healthcare Analytics Preferred

Position Summary

The Senior Data Engineer is a technical authority Analytics Organization data engineering practice. This role takes ownership of complex pipeline design, architectural decisions, and end-to-end delivery accountability for enterprise data integration workflows. Beyond development, the Senior Data Engineer mentors junior engineers, drives platform stabilization in the AWS-migrated workplace, and actively contributes to modernization planning. This individual operates with high autonomy and is expected to resolve the most complex data engineering challenges across a production footprint of ~2,000 stored procedures, ~225 scheduled jobs, and ~40 job streams.

Key Responsibilities

- Lead the design and architecture of enterprise ETL/ELT pipelines, data integration workflows, and transformation frameworks across DB2, SQL Server, and AWS
- Define and enforce data engineering standards coding patterns, naming conventions, error handling, logging, and performance benchmarks
- Architect scalable data integration solutions using IBM DataStage, Oracle GoldenGate, and SQL-based transformation layers
- Evaluate emerging technologies and propose modernization opportunities aligned to Project Catalyst objectives
- Own L2/L3 escalations for complex pipeline failures, data quality issues, and integration incidents across the production footprint
- Manage and optimize IBM Workload Scheduler job streams, dependency chains, and SLA-driven scheduling configurations
- Oversee DB2 and SQL Server platform health object optimization, index management, storage monitoring,



and release governance
- Lead monthly release cycles end-to-end including environment coordination, change control, and production readiness validation
- Drive automation of high-volume manual tasks — dataset refreshes, extract modifications, and scheduled distribution workflows
- Maintain comprehensive data lineage documentation, pipeline dependency maps, and transformation logic runbooks
- Define and implement data validation frameworks and reconciliation controls across critical pipeline assets
- Lead documentation efforts for runbooks, standard operating procedures, onboarding guides, and disaster recovery playbooks
- Support rebadged workforce integration by transferring institutional knowledge and onboarding new team members
- Partner with Tableau and BusinessObjects developers, business analysts, and domain leads to ensure data reliability for reporting
- Proactively communicate pipeline status, capacity constraints, and delivery timelines to the Analytics Delivery Manager
- Support CSAT improvement by resolving data trust and availability issues that create friction for end-user analytics

Required Qualifications

- Minimum Degree Required: Bachelor’s Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field




- 5-8 years of data engineering experience with deep expertise in ETL/ELT development, pipeline architecture, and enterprise data integration
- Expert-level SQL proficiency in IBM DB2 and/or SQL Server — complex queries, stored procedures, performance tuning, and schema design
- Hands-on IBM DataStage experience including job design, parallel processing, and enterprise deployment
- Strong experience with IBM Workload Scheduler or equivalent enterprise job scheduling platforms
- Proficiency in Oracle GoldenGate or equivalent CDC/replication technologies
- Demonstrated experience in AWS data services — S3, Glue, RDS, Redshift, or Lambda — in a production data engineering context
- Proven ability to lead technical design, conduct reviews, and mentor junior engineers
- Strong RCA and troubleshooting skills across complex, multi-system data environments
- Experience in regulated environments with HIPAA, audit trail, and data access control requirements

Preferred Qualifications

- Healthcare data engineering experience — claims processing, clinical data (HL7/FHIR), EMR integration, or population health pipelines
- AWS certification (Data Engineer – Associate, Solutions Architect, or equivalent)
- Experience with modern data stack tools (dbt, Apache Airflow, Spark) as part of a modernization roadmap
- Familiarity with Tableau or BusinessObjects data source architecture and performance optimization
- Knowledge of HITRUST, CMS reporting requirements, or healthcare regulatory data standards
- Experience supporting on-premises to AWS cloud migration for enterprise data platforms

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