Medical Guardian

Data Engineer

Medical Guardian

full-time

Posted on:

Origin:  • 🇺🇸 United States • Pennsylvania

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Job Level

Mid-LevelSenior

Tech Stack

AzureCloudETLPythonSQL

About the role

  • Medical Guardian is a trusted leader in personal safety solutions delivering independence for aging adults; serves over 625,000 members.
  • Build and maintain ELT pipelines and data models using dbt to support a reliable and scalable enterprise data warehouse.
  • Collaborate with data architects and other engineers to implement efficient data structures for business reporting, analytics, and AI needs.
  • Prepare and transform datasets for machine learning models and automate model inputs/outputs to enable data-driven products.
  • Develop and orchestrate data workflows using Azure Data Factory, Azure SQL, Synapse Analytics, and Blob Storage.
  • Ensure scalability, performance, data integrity, validation, testing, and monitoring across pipelines.
  • Follow internal data governance and compliance policies including HIPAA and CCPA.
  • Partner with cross-functional stakeholders; participate in code reviews, documentation, and sprint planning.
  • Hybrid role requiring a minimum of two days per week in the Philadelphia office and occasional off-hours troubleshooting.

Requirements

  • Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field.
  • 3+ years of professional experience in data engineering or a similar role supporting data infrastructure and analytics solutions.
  • Must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.
  • Proficient in SQL, Python, and dbt for transformation and modeling.
  • Hands-on experience with Azure Data Factory, Azure SQL, Synapse Analytics, and Blob Storage.
  • Familiarity with ELT/ETL best practices, dimensional modeling, and building pipelines for modern data warehouses.
  • Experience supporting machine learning model development or deployment (preferred).
  • Familiarity with MLOps workflows, CI/CD for data pipelines, and Git-based version control (preferred).
  • Background in regulated environments such as healthcare or financial services is a plus.
  • Willingness to assist with off-hours production troubleshooting as needed.
  • Knowledge of data governance and compliance requirements (HIPAA, CCPA).