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WE ARE RESILIENT CO. We adapt to your needs.
Data Engineer – Salesforce/SAP
Location
Argentina
Posted
51 days ago
Salary
0
Seniority
Senior
Job Description
Data Engineer – Salesforce/SAP
Resilient Co.
• Own the end-to-end data quality backlog: intake, analysis, prioritization, definition, tracking, and closure. • Define severity/impact criteria (patient, compliance, operational, reporting) and SLAs with key stakeholders. • Perform root cause analysis for issues such as duplicates, missing/invalid values, inconsistent definitions, referential integrity problems, mapping errors, and out-of-standard data. • Implement remediation actions: validation rules, deduplication, normalization, reconciliation, and preventive monitoring. • Design and maintain data quality controls (tests, rules, scorecards) and alerting to prevent recurrence. • Work confidently with standard/custom objects, relationships, security/access model considerations, integrations, and processes impacting data quality. • Ensure solutions follow Salesforce data management standards and best practices (governance, naming conventions, ownership, stewardship, lineage/traceability where applicable). • Collaborate with PO/BA/Engineers/QA to turn data issues into actionable Salesforce-related data quality user stories. • Lead/participate in refinement: scope definition, acceptance criteria, test approach, release plan, and validation. • Support execution and verify outcomes in lower environments and production. • Provide guidance and recommendations on data strategy, data management standards, and sustainable quality practices. • Propose a 2026 roadmap of quick wins and structural improvements to improve reliability and reduce recurring issues.
Job Requirements
- Proven experience as a Data Engineer working on data quality (identification, prioritization, resolution, prevention).
- Strong understanding of Salesforce and its data model (objects, relationships, integrations, reporting) and industry best practices for Salesforce data management.
- Strong SQL skills for investigation and validation (profiling, complex joins, reconciliation).
- Experience working in Agile teams and managing a backlog (user stories, acceptance criteria, Definition of Done).
- Strong communication skills to explain findings, risks, and impact to technical and non-technical stakeholders.
- Experience with data quality/observability practices: automated tests, monitoring, DQ dashboards/scorecards, alerting.
- Experience with data integration and pipelines (ETL/ELT) and analytics ecosystems (e.g., Python, dbt, Airflow) depending on the stack.
- Familiarity with data governance practices (data catalog, lineage, definitions, stewardship).
- Exposure to healthcare privacy/security or regulatory considerations (e.g., HIPAA), depending on region/client.
Benefits
- Health insurance
- Professional development opportunities
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