Senior Data Engineer IS - Remote
$61.31 - $104.39 per hourProvidence
Senior Data Engineer IS (DataOps) Providence caregivers are not simply valued – they’re invaluable. Join our team at Enterprise Information Services and thrive in our culture of patient-focused, whole-person care built on understanding, commitment, and mutual respect. Your voice matters here, because we know that to inspire and retain the best people, we must empower them. The Senior Data Engineer is responsible for designing and developing modern, data-centric applications that support clinical and operational workflows across the healthcare system. These solutions leverage cloud technologies, big data platforms, data science methodologies, and contemporary software development frameworks. Key responsibilities include building scalable data pipelines, transformation and enrichment processes, provisioning layers, and intuitive user interfaces aligned with strategic initiatives. This role also involves mentoring junior Data Engineers and contributing to the research and adoption of emerging technologies to establish repeatable processes and templates. Collaboration is a core value, with a strong emphasis on thorough source control and documentation. The ideal candidate approaches complex challenges with simplicity, utilizing modern tools and techniques to deliver efficient solutions. This position works closely with Product, Platform, and Architecture teams to ensure alignment Providence supports 100% virtual work for residents located in the following areas:
- Alaska
- Washington
- Oregon
- Montana
- California
- Texas: Lubbock
- Texas: Levelland
- Texas: Plainview
- Optimizing Snowflake performance and spend (warehouses, caching).
- Enforcing access controls and secrets management, supporting compliance and
- 8 or more years of data development experience
- 5 or more years of production data operations experience
- Strong SQL, plus hands-on Python and shell scripting (Bash/PowerShell) on
- Experience with cloud computing and data warehousing on relational platforms
- Solid understanding of OLAP/dimensional modeling and RDBMS fundamentals
- Knowledge of semi/unstructured data (JSON/Parquet) and API integrations
- Familiarity with open-source ELT/ETL tooling.
- Git-based workflows and CI/CD basics for data deployments
- Experience building and managing data ingestion pipelines from multiple
- Streamlit for lightweight internal apps and operational dashboards
- Experience with enterprise schedulers (e.g., Ctrl-M) and
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