SAP Data Migration Engineer

Job not on LinkedIn

🕒 March 12

🇺🇸 United States – Remote

💵 $98k - $127.8k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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General Dynamics Information Technology

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1954

🔒 Cybersecurity

🤖 Artificial Intelligence

Defense • Cybersecurity • Artificial Intelligence

General Dynamics Information Technology is a company at the forefront of technological innovation, offering a wide range of services including consulting, digital modernization, and application services. The company is heavily involved in implementing solutions related to artificial intelligence, cloud computing, cybersecurity, high-performance computing, and quantum technologies. GDIT is committed to supporting government and defense sectors, providing mission-critical services such as logistics and supply chain management, intelligence, and homeland security. The company also focuses on diverse and inclusive hiring practices and actively promotes employee well-being. Through its digital accelerator solutions and pioneering use of emerging technologies, GDIT aims to propel agencies' missions forward and address complex technological challenges.

📋 Description

• Execute data extractions from SAP ECC using SAP Data Services (BODS). • Query and analyze source and staging data using SAP HANA SQL. • Build, maintain, and optimize dataflows, workflows, and extraction jobs. • Perform source data analysis and data profiling to identify data quality issues. • Perform source to target field-level data mappings. • Apply transformation rules, derivations, and validations within SAP Data Services. • Translate functional mapping specifications into executable ETL logic. • Load master and transactional data into SAP S/4HANA using Migration Cockpit and LSMW. • Execute mock loads and support cutover load activities. • Analyze load errors, correct data issues, and reprocess loads as required. • Validate data across source systems, staging, and S/4HANA targets. • Reconcile record counts, balances, and key attributes based on defined validation criteria. • Support defect resolution and retesting during mock cycles. • Identify data quality issues such as duplicates, missing values, and invalid formats. • Support cleansing activities in coordination with business data owners. • Implement data correction logic within SAP Data Services where applicable. • Support mock load cycles, dress rehearsals, and production cutover execution. • Execute data loads according to defined load waves, object sequencing, and cutover schedules. • Perform root-cause analysis of load and validation errors across BODS, Migration Cockpit, and HANA layers. • Maintain and update mapping specifications and transformation logic documentation. • Track, analyze, and remediate data defects using defined defect management processes. • Validate data readiness prior to load execution (completeness, format, dependencies). • Work with functional teams to resolve data issues tied to configuration or business rules.

🎯 Requirements

• 8+ years of related experience • Bachelor’s degree in computer science, information technology, or a related discipline • Strong experience with SAP Data Services (BODS) • Working experience with SAP HANA backend • Practical experience using S/4HANA Migration Cockpit, LSMW & BDC • Demonstrated experience with data extraction, mapping, transformation, and validation • Working knowledge of SAP master data objects (Customer, Vendor, Material, GL) • Experience handling large datasets and flat-file-based loads • Deep knowledge of SAP Table structures. • US Citizenship Required: Yes

🏖️ Benefits

• 401K with company match • Comprehensive health and wellness packages • Internal mobility team dedicated to helping you build your skills and own your career • Professional growth opportunities include paid education and certifications • Cutting-edge technology you can learn from • Rest and recharge with paid vacation and 10 company-paid holidays • GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period