Senior Data Engineer

Medical Guardian•Philadelphia, PA

16d•Hybrid

About The Position

Medical Guardian is a fast-growing digital health and safety company dedicated to helping people live without limits. With a strong track record of growth, we are transforming the experience of aging confidently and independently. We serve over 625,000 members nationwide with emergency response systems and remote patient monitoring. Our culture is built on innovation, compassion, and purpose. This role is specifically designed to develop real-time streaming data solutions that support data-driven decisions for live devices and telemetry data. While the Senior Data Engineer will also contribute to batch data processes, the primary focus will be on real-time streaming use cases, creating data services for APIs and microservices, and building pipelines for operational applications and ML/AI model development within a medical device IoT context.

Requirements

Bachelor's degree in Computer Science, Mathematics, Engineering, or a related technical field and 6+ years of professional experience in data engineering, analytics, or warehousing OR Master's degree in a related technical field and 3+ years of professional experience in data engineering, analytics, or warehousing
5+ years of experience designing, building, and operating big data and real-time streaming pipelines across cloud and on-premises environments
5+ years applying DevOps and CI/CD practices to data and analytics workloads
Production experience building data services, APIs, or microservices for downstream data consumption
Strong, hands-on experience designing and building production-grade data pipelines on Databricks
Demonstrated experience with Spark optimization and tuning in Databricks, including performance analysis, partitioning strategies, caching, shuffle optimization, and cost-aware pipeline design
Strong experience with Azure cloud services for data engineering and streaming workloads
Experience building data services, APIs, or microservices for data consumption.
Data quality, validation, and privacy-aware handling for regulated or sensitive data
Candidates must be authorized to work in the United States without current or future need for visa sponsorship.
Candidates must be able to commute to our Philadelphia, PA office on Tuesdays and Wednesdays.

Nice To Haves

Azure Event Hubs and Azure Stream Analytics for IoT and telemetry ingestion and stream processing
Additional Azure data and integration services supporting batch and streaming architectures
Collaboration with ML teams: feature pipelines, training data, or streaming data for model development

Responsibilities

Design and build batch and streaming data pipelines on Azure and Databricks, with primary focus on real-time IoT and telemetry use cases within a Medallion architecture.
Develop ETL/ELT workflows to ingest, transform, and validate large volumes of structured and unstructured data.
Build and maintain data services, APIs, and microservices for application, analytics, and ML/AI teams.
Implement real-time streaming solutions using Azure Event Hubs, Azure Stream Analytics, and related Azure integration patterns, with cost-effective throughput, partitioning, and downstream delivery to Databricks.
Optimize production Databricks pipelines using PySpark, Spark SQL, and Delta Lake, including Spark tuning for performance, reliability, and cost.
Troubleshoot and resolve complex pipeline issues across Databricks, Azure, and on-premises systems, including root cause analysis and corrective action.
Partner with data analysts, software engineers, ML engineers, and business stakeholders to translate requirements into technical designs and delivery priorities.
Apply data quality, validation, and privacy-first practices, and deliver reliable pipelines through software engineering standards, documentation, testing, and CI/CD.