Data Engineer

Data Engineer I

This position focuses on expanding and optimizing the healthcare system’s data and data pipeline architecture, overseeing data flow and collection for cross‑functional teams. The Data Engineer design, builds, and maintains scalable data infrastructure to support clinical, operational, and strategic decision‑making. Reporting to the Director of Data Intelligence and Decision Science, the role collaborates with data scientists, analysts, software engineers, and clinical informatics teams.

It ensures data quality, security, and accessibility by integrating data from sources such as EHRs, medical devices, financial systems, and external partners. The Data Engineer is critical to enabling predictive analytics, population health management, and regulatory compliance.

• Creates and maintains optimal data pipeline architecture for structured and unstructured healthcare data.
• Assembles large, complex data sets that meet functional and non‑functional business requirements.
• Builds scalable ETL/ELT pipelines using SQL and AWS big data technologies.
• Optimizes pipeline performance for latency, throughput, and fault tolerance.
• Ensures pipelines comply with HIPAA and other regulatory standards.

• Builds infrastructure for optimal extraction, transformation, and loading of data from diverse sources.
• Creates and maintains data lakes, warehouses, and marts using platforms like Snowflake, Redshift, or Big Query.
• Configures cloud‑based storage and compute environments (AWS, Azure, GCP).
• Implements schema design, indexing, and partitioning strategies.
• Ensures high availability and disaster recovery protocols.

• Creates data tools for analytics and data science teams to build and optimize data products.
• Develops reusable components for reporting and dashboarding tools.
• Builds data models and views for use by analysts and data scientists.
• Enables self‑service analytics through curated datasets.
• Collaborates with stakeholders to define KPIs and metrics.

• Identifies, designs, and implements internal process improvements.
• Automates manual processes and optimizes data delivery.
• Re‑designs infrastructure for greater scalability and performance.
• Refactors legacy systems for maintainability.
• Implements CI/CD pipelines for data workflows.

• Works with stakeholders including Executive, Product, Data, and Design teams to support data infrastructure needs.
• Translates business requirements into technical specifications.
• Provides mentorship to junior data engineers.
• Communicates technical concepts to non‑technical stakeholders.
• Supports cross‑functional initiatives and agile squads.

• Keeps data separate and secure, following all relevant governance and security protocols.
• Implements data validation, anomaly detection, and cleansing routines.
• Collaborates with data governance teams to enforce policies.
• Audits data for completeness, accuracy, and timeliness.
• Supports data stewardship and master data management initiatives.

• Conducts training sessions for analysts and clinical staff on data tools.
• Participates in vendor evaluations and proof‑of‑concept projects.
• Supports data integration for mergers, acquisitions, or new service lines.
• Assists in disaster recovery drills and business continuity planning.
• Contributes to grant proposals or research initiatives requiring data support.
• Performs related duties as required.

• Quickly learns new technical skills and knowledge; adopts new data tools and frameworks with minimal supervision.
• Learn and apply healthcare‑specific data standards (e.g., HL7, FHIR).
• Keeps current with cloud platform updates and best practices.

• Uses rigorous logic and methods to solve difficult problems with effective solutions.
• Diagnoses root causes of data pipeline failures.
• Designs scalable solutions for complex data integration challenges.
• Applies statistical methods to validate data quality.

• Possesses the functional and technical knowledge and skills to do the job at a high level of accomplishment.
• Writes efficient SQL and Python code for data processing.
• Configures cloud infrastructure for data workloads.
• Implements secure and compliant data architectures.

• Copes with change effectively; can shift gears…