Data Engineer - Remote
About The Position
Sentara is hiring a Data Engineer to support a modern data platform built on Databricks. This fully remote role focuses on building scalable data pipelines, supporting a metadata-driven ingestion framework, and embedding data quality and governance into the platform. Remote work is available to candidates located in the states listed in the posting. The role involves developing and maintaining pipelines with PySpark and Databricks, onboarding datasets through a metadata-driven framework, implementing validation and data-quality checks, processing file-based sources and ingestion-tool feeds, and addressing schema changes and incremental loads. The Data Engineer also contributes to governance practices, resolves pipeline failures and performance issues, and collaborates with architects and stakeholders on onboarding and requirements. A bachelor’s degree is not required if the candidate has the stated equivalent experience. The posting lists 3+ years of relevant experience with a degree or 5+ years without a degree, and separately describes required relevant experience as 3 to 5 years. The position offers market-competitive compensation and a comprehensive benefits package. The posting contains two different full-time base-pay ranges: $80,204.80–$133,681.60 and $101,670.40–$155,750.40 annually.
Requirements
- Relevant experience: 3+ years with a degree or 5+ years without a degree; the posting also states a requirement of 3 to 5 years of relevant experience.
- Hands-on experience with PySpark and Databricks.
- Strong SQL skills.
- Experience building ETL/ELT data pipelines.
- Understanding of Delta Lake concepts, including merge, schema evolution, and partitions.
- Familiarity with cloud platforms.
- Basic experience with Git and version control.
- Exposure to data catalog or governance tools, such as DataHub.
- Experience with Fivetran or similar ingestion tools.
- Understanding of data-quality and validation concepts.
- Experience working with metadata-driven frameworks.
- Strong problem-solving and debugging skills.
- Ability to work in a structured, framework-driven environment.
- Focus on data quality, not just pipeline execution.
- Willingness to learn and adapt in a fast-evolving data ecosystem.
Nice To Haves
- Azure is the preferred cloud platform.
Responsibilities
- Develop and maintain data pipelines using PySpark and Databricks.
- Use a metadata-driven ingestion framework to onboard new datasets.
- Implement data-quality checks and validation rules in pipelines.
- Support ingestion from file-based sources and ingestion tools such as Fivetran.
- Handle schema changes, incremental loads, and file-processing patterns.
- Contribute to data governance practices, including tagging, metadata, and lineage.
- Troubleshoot and resolve pipeline failures and performance issues.
- Collaborate with architects and stakeholders on data onboarding and requirements.
- Follow and contribute to coding standards, reusable components, and best practices.
Benefits
- Medical, dental, and vision plans.
- Adoption, fertility, and surrogacy reimbursement up to $10,000.
- Paid time off and sick leave.
- Paid parental and family caregiver leave.
- Emergency backup care.
- Long-term and short-term disability and critical illness plans.
- Life insurance.
- 401(k)/403(b) with employer match.
- Tuition assistance of $5,250 per year and discounted educational opportunities through Guild Education.
- Student debt pay down up to $10,000.
- Pet insurance.
- Legal resources plan.
- Opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria are met.
- Paid holidays.
- Paid military leave.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
