Job Description
Title: Data Engineer - DataStage ETL Location: 100% Remote Duration: 8+ Months with possible extensions Technical Skills - Must Have - 3 + years of experience in ETL space
- 3+ years of proven experience with IBM DataStage.
- Business Intelligence - Systems/ETL
- SQL
Nice To Have - Python
- Salesforce
- Snowflake
Job Summary: We are seeking a Senior Data Engineer to execute end-to-end Salesforce data migrations. Data will be moved from Snowflake to on-premise systems to DataStage and then to Salesforce. This role focuses on source-to-target mapping, IBM DataStage-driven ETL development, data cleansing and validation, mock migration runs, cutover execution, and post-load reconciliation. You will collaborate closely with Salesforce administrators, solution architects, product owners, and SMEs to deliver repeatable, auditable, and automation-ready migration processes.
Key Responsibilities - Develop source-to-target mapping specifications including field-level transformations, deduplication logic, and validation rules.
- Build and configure ETL workflows using IBM DataStage, SQL, and Python to automate extraction, transformation, and loading into Salesforce.
- Profile source data; assess data quality issues; implement cleansing and standardization routines.
- Execute mock migration runs, capture error logs, perform root-cause analysis, and implement remediation steps.
- Perform final production data loads and verifications with business sign-off.
- Produce reconciliation reports to validate accuracy, completeness, and referential integrity post-migration.
- Author a comprehensive migration runbook covering workflows, schedules, controls, rollback, and support procedures.
- Implement quality checks, lineage notes, and audit artifacts aligned to governance and compliance requirements.
- Partner with Salesforce teams to respect object relationships, load order, and platform limits during migrations.
- Contribute to continuous improvement by optimizing ETL performance and automating repetitive validation tasks.
Critical Deliverables - Source-to-target data mapping logic with transformation rules.
- Configured ETL workflows/scripts for extraction, transformation, and loading.
- Validated data extraction files from source Salesforce org (or legacy systems).
- Documented data cleansing and validation rules.
- Test migration runs with error logs and remediation steps.
- MOCK (3) data loads into target Salesforce org with verification.
- Final data load into target Salesforce org with verification.
- Post-migration data quality and reconciliation report.
- Comprehensive migration runbook and documentation.
Required Skills - Hands-on experience with IBM DataStage for ETL/ELT development.
- Strong SQL with proven performance tuning on large datasets.
- Demonstrated ability to perform data mapping, cleansing, deduplication, and validation.
- Working understanding of data governance, quality checks, lineage, and compliance.
- Experience optimizing ETL jobs and troubleshooting data load issues.
Nice to Have - Knowledge of the Salesforce data model (objects, relationships, metadata, constraints).
- Experience with Salesforce Data Loader or comparable migration tools.
- Familiarity with Snowflake or another cloud data warehouse for staging/landing zones.
- Exposure to CI/CD for scheduling and deploying DataStage jobs and Python scripts.
- Proficiency in Python (or similar scripting language) for data manipulation and automation.
Qualifications - Bachelor's degree in Computer Science, Information Systems, or equivalent practical experience.
- 7+ years of data engineering experience, including 3+ years building production ETL pipelines.
- Prior delivery of at least one enterprise CRM or Salesforce migration is strongly preferred.
Job Tags
Remote work