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
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
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
~ Solid 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)

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.

📌 IT Data Architect (Bengaluru)
🏢 PwC
📍 Bengaluru