Datastage Developer ( Pan India - Night Shift)

Job Title: Senior DataStage Developer & Support Specialist Experience: 6+ Years Location: Pan India Shift: Night Shift Job Summary: We are looking for a highly skilled Senior DataStage professional with 6+ years of experience in ETL development and support. The ideal candidate will have expertise in IBM InfoSphere DataStage along with strong knowledge of Snowflake, Databricks,DB2 or other SQL-based databases. The candidate will be working on the project and must be willing to work in US/night shifts to collaborate effectively with global teams. Key Responsibilities: Key Responsibilities Define the enterprise data engineering architecture and technology standards across DB2, SQL Server, IBM DataStage, IBM Workload Scheduler, Oracle GoldenGate, Collibra and AWS Lead the multi-year platform modernization roadmap phased migration from legacy on-premises patterns to cloud-native AWS data engineering patterns Govern platform health including capacity planning, performance benchmarks, upgrade management, and disaster recovery compliance with BCP/DR standards Lead workload rationalization identifying pipelines, stored procedures, and jobs for consolidation, retirement, or re-architecture Evaluate and drive adoption of modern data engineering capabilities (Apache Airflow, dbt, AWS Glue, Spark) aligned to Project Catalyst objectives Own SLA adherence across all data engineering queues incidents, service requests, small-ticket enhancements, and larger backlog-driven work Lead root cause analysis (RCA) for critical data incidents and drive permanent fixes to prevent recurrence Lead monthly release cycles including environment coordination, change control governance, and production readiness sign-off Maintain full backlog visibility in ServiceNow — classification, aging, capacity tracking, and executive-level reporting Define and oversee data quality monitoring frameworks, escalation procedures, and continuous improvement programs Serve as the primary data engineering relationship owner for senior stakeholders across PHP, PDS/PMG, Quality, and System Services Own CSAT measurement and improvement for the data engineering domain, proactively addressing data trust and availability concerns Deliver weekly operational and monthly executive reporting on pipeline health, throughput, SLA performance, and platform KPIs Develop and own the multi-year data engineering roadmap aligned to Project Catalyst's stabilization-to-modernization progression Lead the phased AWS cloud migration strategy for remaining on-premises data engineering components, ensuring continuity and minimal disruption Identify and implement automation opportunities to reduce manual pipeline interventions, refresh datasets, and extract requests Lead knowledge management across the engineering team — runbooks, architecture diagrams, onboarding playbooks, and continuity documentation Oversee end-to-end delivery of managed data analytics services to clients, ensuring projects meet business requirements, timelines, and quality standards Monitor and manage service-level agreements (SLAs) and key performance indicators (KPIs). Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions Serve as the primary point of contact for high-level client interactions, maintaining strong relationships. Manage client escalations and ensure timely resolution of issues. Required Qualifications Minimum Degree Required: Bachelor’s Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field 8+ years of data engineering experience with deep expertise in enterprise ETL/ELT architecture, pipeline design, and large-scale data platform operations 3+ years in a formal lead, manager, or technical lead capacity overseeing a data engineering team Expert-level SQL proficiency in IBM DB2 and SQL Server including complex schema design, query optimization, and stored procedure management Expert-level IBM DataStage experience including architecture, parallel job design, performance tuning, and enterprise deployment Deep expertise in IBM Workload Scheduler — complex job stream design, dependency management, SLA configuration, and production operations Advanced Oracle GoldenGate experience including replication architecture, CDC design, and production support Proven AWS data engineering experience in production — S3, Glue, RDS, Redshift, Lambda, and IAM-governed data access Demonstrated ability to develop and execute multi-year technology roadmaps and lead platform modernization programs Experience leading managed services or outsourced delivery models with SLA, CSAT, and throughput accountability Preferred Qualifications Healthcare data engineering experience across claims, clinical (HL7/FHIR), EMR, pharmacy, population health, or regulatory reporting domains AWS certification — Data Engineer Professional, Solutions Architect Professional, or equivalent Experience with modern data stack adoption in enterprise settings — Apache Airflow, dbt, Spark, Delta Lake, or equivalent Knowledge of HIPAA, HITRUST, CMS, and healthcare data regulatory compliance requirements Experience leading on-premises to cloud migrations for large-scale enterprise data platforms Familiarity with Tableau, BusinessObjects, or SAS as downstream analytics consumers of engineered data Background in agile delivery, DevOps practices, and CI/CD pipelines for data engineering