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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: Bachelors 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, Informatica, SSIS, or equivalent) 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.