Data Engineer
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Job Description
Project Manager leading SaaS implementations at InductiveHealth, focusing on public health solutions through technology. Collaborating with teams for successful project delivery and client engagement.
Responsibilities:
- Lead the continued transition of legacy SAS-based ETL processes to SQL Server, completing remaining migrations and validating results through parallel processing and data reconciliation.
- Translate undocumented or minimally documented legacy ETL logic into maintainable, fault tolerant SQL Server and SSIS workflows.
- Improve and standardize incremental data processing patterns, reducing reliance on full data refreshes and destructive reload processes.
- Own the reliability and performance of ETL pipelines by identifying and resolving bottlenecks, particularly in high-volume and performance-sensitive workflows.
- Investigate and correct data flow issues that prevent records from consistently reaching downstream systems across environments.
- Support production data operations by partnering with product, engineering, and support teams to triage and resolve data-related issues and support tickets.
- Participate in regular operational check-ins and serve as a primary escalation point for ETL and data pipeline concerns.
- Document ETL logic, dependencies, and operational processes to reduce institutional knowledge risk and improve long-term maintainability.
- Introduce improved logging, monitoring, automation, and repeatability across data integration workflows.
- Collaborate with engineering peers and domain experts to establish clearer ownership and standards for ETL and data pipeline practices.
Requirements:
- Strong hands-on experience with SQL Server development, including advanced T-SQL, query optimization, and performance tuning in production environments.
- Demonstrated experience designing, maintaining, and modernizing data pipelines and ETL processes, particularly in environments transitioning from legacy architectures to more scalable, maintainable data platforms.
- Ability to analyze, interpret, and translate legacy data transformation logic (including SAS-based workflows) into modern, SQL-based implementations, with an emphasis on clarity, performance, and long-term maintainability.
- Experience with SQL Server–based data integration tooling or comparable modern data orchestration frameworks, including support for incremental processing, dependency management, and multi-step pipelines.
- Familiarity with modern data engineering concepts such as idempotent pipelines, incremental ingestion patterns, schema evolution, and environment-aware deployments.
- Comfort working within complex, partially undocumented systems and progressively improving them through refactoring, documentation, and automation.
- Experience supporting and operating production data pipelines, including diagnosing failures, resolving data quality issues, and partnering cross-functionally to restore and improve system reliability.
- Experience managing data workflows across multiple environments (development, scale, production) with attention to consistency, validation, and release coordination.
- Strong problem-solving skills with a systems-level mindset, particularly when identifying root causes of performance, scalability, or data integrity issues.
- Ability to work collaboratively with engineering, product, and support teams while maintaining clear ownership of data platform outcomes.
- Clear written and verbal communication skills, especially when documenting technical systems and explaining data flows to both technical and non-technical stakeholders.
Benefits:
- Virtual first, remote organization and culture
- Flexible Paid Time Off (PTO)
- 401(k) retirement plan with corporate matching
- Medical, prescription, vision, and dental coverage (multiple plans based on your needs)
- Short Term and Long Term Disability (for employee)
- Life Insurance (for employee)
- New Team Member support for home office setup
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