Data Engineer

Medical Guardian is a trusted leader in personal safety solutions to deliver independence for aging adults. Serving over 625,000 members, we provide innovative technology and compassionate support to help individuals live confidently and securely.

We are seeking a Data Engineer to join our AI & Analytics team. This role will be a key contributor to the ongoing development and maintenance of our enterprise data warehouse. The Data Engineer will focus on building data models, creating transformation pipelines, and supporting analytics and AI/ML use cases across the organization. 

Working closely with data scientists, AI engineers, and business stakeholders, this individual will ensure the accuracy, scalability, and availability of trusted data through tools like dbt, SQL, and Azure data services. 

Key Responsibilities: 

Data Engineering & Warehouse Support 

• 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 that serve business reporting, analytics, and AI needs.
• Ensure performance, data integrity, and documentation for the pipelines that feed into and out of the data warehouse.

AI/ML Enablement 

• Prepare and transform datasets for machine learning models and AI agents, supporting feature engineering and model deployment.
• Work with AI engineers and data scientists to automate model inputs/outputs and enable data-driven products.

Azure Data Platform Integration 

• Develop and orchestrate data workflows using Azure Data Factory, Azure SQL, Synapse Analytics, and Blob Storage.
• Ensure the scalability and operational stability of data processes running in the Azure cloud.

Data Quality & Governance 

• Implement data validation, testing, and monitoring across pipelines to maintain trust in critical datasets.
• Follow internal data governance and compliance policies including HIPAA and CCPA requirements.

Collaboration & Continuous Improvement 

• Partner with cross-functional stakeholders including product managers, analysts, and IT teams to understand data requirements.
• Participate in code reviews, documentation efforts, and sprint planning to contribute to team-level success.

Qualifications 

Education and Experience:

• 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 solution.

Technical Expertise:

• Proficient in SQL, Python, and dbt for transformation and modeling.
• Hands-on experience with Azure cloud services, including Data Factory, Synapse Analytics, Azure SQL, and Blob Storage.
• Familiarity with ELT/ETL best practices, dimensional modeling, and building pipelines for modern data warehouses.

Additional Preferred Skills: 

• Experience supporting machine learning model development or deployment.
• Familiarity with MLOps workflows, CI/CD for data pipelines, and Git-based version control.
• Background in regulated environments such as healthcare or financial services is a plus.

Work Hours and Travel Requirements:

You must be open to assisting in troubleshooting and analysis in the event of off-hours production problems, as needed. The IT Team works in a hybrid environment that requires a minimum of two days per week in the Philadelphia office.

• Health Care Plan (Medical, Dental & Vision)
• Paid Time Off (Vacation, Sick Time Off & Holidays)
• Company Paid Short Term Disability and Life Insurance
• Retirement Plan (401k) with Company Match