CBTS is seeking a Lead Data Engineer to oversee and guide complex, enterprise scale Salesforce data migration initiatives. This hands-on leadership role involves technical design, execution oversight, and coordination across various teams to ensure accurate and compliant data migrations.
Responsibilities:
- Own 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 technical decision-maker for mapping logic, transformation patterns, validation strategies, and DataStage/Python ETL design
- Provide guidance, reviews, and sign off on mapping documents, data cleansing rules, and ETL workflows developed by senior and mid-level engineers
- Oversee and coordinate all migration phases: profiling, mapping, extraction, transformation, cleansing, mock runs, remediation, final load, and post load reconciliation
- Lead the creation of repeatable migration templates (mapping patterns, validation scripts, transformation libraries, reconciliation frameworks)
- Troubleshoot the most complex DataStage ETL issues, load failures, and Salesforce API constraints
- Partner closely with Salesforce architects to determine object load order, relationship handling, and platform constraints
- Work with business SMEs to validate mapping logic, resolve data issues, and approve reconciliation reports
- Coordinate across Salesforce, infrastructure, release management, and governance teams to align dependencies and cutover planning
- Define and enforce data validation rules, DQ acceptance thresholds, rejection criteria, and reconciliation metrics
- Ensure compliance with metadata, lineage, audit, and regulatory standards
- Drive defect management workflows for mock runs and ensure timely root-cause resolution
- Oversee and approve the migration runbook, including workflows, controls, schedules, rollback strategies, and support procedures
- Ensure all engineers document mappings, transformation rules, cleansing logic, and validation designs to project standards
- Mentor DataStage developers, senior engineers, and analysts on transformation logic, debugging, and best practices in migration engineering
- Lead technical reviews and provide ongoing coaching to uplift the team’s maturity and consistency
- Approved end to end migration solution design (mapping strategy, transformation patterns, load sequence)
- Final sign off on:
- Source-to-target mappings
- Transformation logic
- Cleansing & validation rules
- Data extraction frameworks
- ETL designs (DataStage/Python)
- Oversight and acceptance of 3 mock migration runs
- Decision authority on defect triage and remediation approach
- Final production load execution leadership + verification sign-off
- Post-migration reconciliation and executive ready reporting
- Complete, approved migration runbook ready for audit or reuse
Requirements:
- Expert-level experience designing and overseeing ETL workflows using IBM DataStage
- Advanced SQL, including performance tuning, complex joins, windowing, and large-volume optimization
- Strong Python skills for automation, validation scripting, data corrections, and transformation logic
- Deep experience performing mapping, cleansing, deduplication, validation, and reconciliation for large datasets
- Strong command of data governance (DQ rules, lineage, controls, audit requirements)
- Strong understanding of Salesforce data model (objects, relationships, lookups, constraints, metadata)
- Experience leading migrations using Data Loader, Bulk API, or other Salesforce ingestion tooling
- Experience designing load ordering strategies and resolving hierarchical or relational dependencies
- Proven experience leading data migration workstreams or teams
- Ability to drive technical decisions and mentor engineers
- Strong communication and stakeholder alignment skills
- nCindo Experience
- Experience with cloud data platforms (Snowflake/Azure/AWS) for staging/pre-processing
- Familiarity with CI/CD for scheduling DataStage/ETL pipelines
- Experience in banking, regulatory, or compliance-driven data migrations