Data Engineer - DataStage ETL IV

Job Summary

The Lead Data Engineer will provide technical leadership and execution oversight for complex, enterprise‑scale Salesforce data migration initiatives. This role is responsible for guiding solution design, ensuring quality and compliance, and directing all phases of the migration lifecycle—from data profiling and mapping through extraction, transformation, validation, mock runs, cutover, and reconciliation.

The position requires close collaboration with Salesforce architects, business subject‑matter experts, Data Stage developers, enterprise data teams, and project leadership to ensure migrations are accurate, scalable, repeatable, and fully documented. This is a hands‑on leadership role that involves designing, reviewing, troubleshooting, and building key components while supporting and guiding other engineers.

Job # 3020780

• Job Title:
  
  Data Eng.
  
  - Data Stage ETL IV
• Location:
  
  Remote (EST)
• Pay Range: $87-$94
• Length: 8 Months

• Lead the end‑to‑end technical design of Salesforce migration pipelines, including load strategy, dependency sequencing, staging architecture, and data quality controls.
• Serve as the primary decision‑maker for mapping logic, transformation patterns, validation strategies, and Data Stage/Python ETL design.
• Review, guide, and approve mapping documents, data cleansing rules, and ETL workflows produced by engineering team members.

• Oversee all migration phases: profiling, mapping, extraction, transformation, cleansing, mock runs, remediation, final load, and post‑load reconciliation.
• Develop reusable migration templates, including mapping patterns, validation scripts, transformation libraries, and reconciliation frameworks.
• Troubleshoot complex Data Stage ETL issues, load failures, and Salesforce API limitations.

• Collaborate with Salesforce architects to define object load order, relationship handling, and platform constraints.
• Work with business SMEs to validate mapping logic, resolve data issues, and approve reconciliation results.
• Coordinate with Salesforce, infrastructure, release management, and governance teams to align dependencies and cutover activities.

• Establish and enforce data validation rules, data‑quality thresholds, rejection criteria, and reconciliation metrics.
• Ensure adherence to metadata, lineage, audit, and regulatory requirements.
• Lead defect‑management processes during mock runs and ensure timely root‑cause resolution.

• Oversee and approve the migration runbook, including workflows, controls, schedules, rollback strategies, and support procedures.
• Ensure comprehensive documentation of mappings, transformation rules, cleansing logic, and validation designs.

• Mentor Data Stage developers, senior engineers, and analysts on transformation logic, debugging, and migration best practices.
• Lead technical reviews and provide coaching to strengthen team capability and consistency.

• Approved end‑to‑end migration solution design, including mapping strategy, transformation patterns, and load sequencing.
• Final sign‑off on:
  • Source‑to‑target mappings
  • Transformation logic
  • Cleansing and validation rules
  • Data extraction frameworks
  • ETL designs (Data Stage/Python)
• Oversight and acceptance of three mock migration cycles.
• Decision authority for defect triage and remediation.
• Leadership of final production load and verification.
• Post‑migration reconciliation and executive‑level reporting.
• Completed and approved migration runbook suitable for audit or reuse.

• Expert‑level experience designing and managing ETL workflows using IBM Data Stage.
• Advanced SQL skills, including performance tuning, complex joins, windowing, and optimization for large datasets.
• Strong Python capabilities for automation, validation scripting, data corrections, and transformation logic.
• Extensive experience with mapping, cleansing, deduplication, validation, and reconciliation of large datasets.
• Strong understanding of data governance, including data‑quality rules, lineage, controls, and…