Technical Lead-Data Engg

Area(s) of responsibility

Data Engineer (Migration Consultant)

Role Summary

We are seeking a Senior Data Engineer with strong enterprise data migration experience to own the end-to-end data pipeline — from source extraction through transformation, cleansing, validation, and final loading into the target ERP system. The candidate should bring deep expertise in ERP data structures, data quality processes, and iterative migration execution.

Key Responsibilities

• Design and build data extraction pipelines from source ERP systems; manage data ingestion into cloud-based staging environments; validate completeness and structure post-extraction.
• Execute data profiling and analysis; prepare source-to-target mapping workbooks and data dictionaries for business review and sign-off.
• Apply cleansing, standardization, and validation rules to master and transactional data objects; manage exception handling and remediation workflows.
• Execute enrichment processes to address missing or incomplete data attributes; coordinate with functional stakeholders on data quality decisions.
• Run deduplication processes; apply survivorship logic; produce consolidated golden records for business approval.
• Build transformation pipelines to convert cleansed data into target-system import formats (IDOCs, BAPIs, flat files, or API payloads); manage sequencing and load dependencies.
• Execute data loads into the target ERP system; perform post-load reconciliation — source-to-target variance analysis, fallout reporting, and correction logging.
• Maintain detailed documentation — mapping workbooks, profiling reports, transformation specifications, reconciliation reports, and audit trails.
• Contribute to building reusable pipeline logic and migration assets for efficiency in future execution cycles.
  
  

• 6–8 years in data engineering or data migration, with at least 3+ years on enterprise ERP migration projects.
• Strong understanding of ERP data structures — master data (Item, Vendor, Customer, BOM) and transactional data (PO, SO, Invoices, Inventory).
• Hands-on experience with ERP data loading mechanisms — IDOCs, BAPIs, LSMW, batch loaders, APIs, or equivalent import methods.
• Proficiency in SQL and Python/PySpark for data transformation, pipeline development, and automation.
• Experience with cloud data services — AWS (S3, Glue, Redshift), Azure (Data Factory, Synapse), or Databricks for building scalable data pipelines.
• Strong expertise in data quality disciplines — profiling, cleansing, standardization, deduplication, enrichment, and reconciliation.
• Experience with iterative migration execution — Mock, SIT, UAT, and Production load cycles with progressive data coverage.
• Ability to work with AI/ML-generated outputs (mappings, rules, confidence scores) and operationalize them into repeatable pipelines.
• Strong documentation and communication skills — professional mapping workbooks, profiling reports, and reconciliation artifacts.
• Familiarity with version control (Git) and collaborative development workflows.
  
  

• Experience in Healthcare, MedTech, or Life Sciences data migration involving regulated data.
• Familiarity with data governance, lineage, and audit trail requirements for compliance-driven environments.
• Prior experience working in teams that leverage AI/ML for data quality or migration automation.
  
  

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field. Cloud or data certifications (AWS Data, Azure Data Engineer, Databricks) are a plus.