Resilient Co.

Data Engineer – Salesforce/SAP

Resilient Co.

contract

Posted on:

Location Type: Remote

Location: Argentina

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Tech Stack

AirflowETLPythonSQL

About the role

  • 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.

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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data qualitySQLdata integrationETLELTdata governancedata managementdata modelingautomated testsdata pipelines
Soft Skills
communicationcollaborationproblem-solvingleadershipanalytical thinkingprioritizationstakeholder managementguidancerecommendationadaptability