Data Engineer

Key Responsibilities

• Develop, maintain, and optimize SQL-based ETL processes, stored procedures, and data transformations across DB2 and SQL Server environments
• Support and monitor 225 scheduled jobs and 40 job streams using IBM Workload Scheduler, ensuring timely execution and prompt failure resolution
• Build and maintain data pipelines using IBM DataStage and UNIX scripting for enterprise data integration workflows
• Support Oracle GoldenGate for real-time data replication and change data capture (CDC) across source and target systems
• Develop and maintain data integration workflows from source systems to analytics platforms, including validation and reconciliation logic
• Provide operational support for DB2 and SQL Server environments encompassing 160 schemas, 20TB active storage, 4,000 tables, and 3,300 views
• Monitor pipeline health proactively, detect anomalies, and resolve data quality and availability issues within defined SLAs
• Support Dev/QA/Prod environment management including release coordination and production readiness validation
• Assist with AWS stabilization activities for analytics data layers post migration from on-premises infrastructure
• Track and manage all work through ServiceNow, ensuring accurate classification, status updates, and SLA compliance
• Collaborate with Tableau and BusinessObjects developers to ensure data availability and pipeline reliability for reporting
• Participate in L1/L2 triage for pipeline incidents, data quality failures, and integration issues
• Contribute to runbook documentation and standard operating procedures for supported pipelines and jobs

Required Qualifications

• Minimum Degree Required: Bachelor's Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field
• 2-5 years of experience in data engineering, ETL development, or data integration roles
• Strong SQL proficiency — query optimization, stored procedures, and database objects in DB2 and/or SQL Server
• Hands-on experience with at least one enterprise ETL or orchestration tool - IBM DataStage, Netezza
• Experience with job scheduling tools (IBM Workload Scheduler, Control-M, or equivalent)
• Familiarity with UNIX/Linux scripting for pipeline automation and file-based integrations
• Understanding data warehouse concepts — schemas, star/snowflake models, dimensions, and facts
• Ability to troubleshoot data pipeline failures end-to-end and communicate resolution steps clearly
• Experience working in regulated, compliance-aware environments (healthcare preferred)

Preferred Qualifications

• Healthcare data experience — claims, clinical, EMR, pharmacy, or population health datasets
• AWS experience — S3, Glue, RDS, Redshift, or Lambda in a data engineering context
• Experience with Oracle GoldenGate or similar CDC/replication tools
• Familiarity with Tableau or BusinessObjects as downstream consumers of engineered data
• Knowledge of HIPAA data handling requirements and PHI access controls
• Exposure to ServiceNow for ITSM-based delivery tracking.