Senior Data Engineer (Remote)

• Serve as a senior technical advisor and subject matter expert to business customers, architects, and internal teams, solving the most complex data challenges related to healthcare analytics.
• Lead the design and architecture of end-to-end data solutions, translating business requirements into scalable, reusable, and well-documented technical designs.
• Define, drive, and govern data architecture standards, design patterns, and engineering best practices across the data engineering organization.
• Engineer and oversee the preparation of internal and customer-facing datasets, ensuring strict adherence to defined technical specifications, internal data standards, and external Statements of Work (SOWs).
• Architect, develop, and optimize robust, scalable data pipelines to acquire, transform, and provision data for analytics and data science initiatives.
• Design and build performant, scalable data models and warehouse structures within cloud data warehouses (e.g., Google BigQuery, Snowflake) and guide their long-term evolution.
• Partner with SD3 Data Scientists to productionize, operationalize, and manage the handoff of machine learning model inferences into our persistent data stores.
• Establish and champion modern DevSecOps standards, including CI/CD, automated testing, and version control using GitHub, across the team.
• Ensure all data solutions comply with data governance, security policies, and healthcare regulations (e.g., HIPAA), and help define and improve those policies.
• Provide technical leadership and mentorship to junior and mid-level engineers, including leading design reviews and code reviews.
• Lead organizational improvements in processes and technology by evaluating, recommending, and adopting new tools and best practices in data engineering.
• Define and lead unit, integration, and performance testing strategies to ensure the quality, reliability, and scalability of data pipelines.

• 5-8 years of data development experience with a focus on designing and building data pipelines and ETL processes
• 5-8 years of experience with the cloud (AWS, Azure and/or Google Cloud Platform) - GCP experience highly preferred
• 5-8 years of experience in cloud-based data warehouses (Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics)
• 5-8 years of experience with cloud-based ETL/ELT tools (Matillion, Glue, Data Factory). Matillion experience is strongly preferred.
• 2+ years in a technical lead or data/solution architecture capacity, leading the design of large-scale data solutions
• Bachelor’s Degree (Computer Science, Engineering, Information Systems, Mathematics, Business Analytics, or relevant degree)

Preferred Work Experience:

• Experience with version control systems (Git) and leading DevSecOps / CI-CD practices
• Understanding of and willingness to embrace Agile Principles (Scrum), including serving as a technical lead
• Experience mentoring engineers and conducting design and code reviews
• Experience defining data architecture standards and data governance across teams
• Physical and Mental Requirements:
• Open mindset, ability to quickly adapt new technologies and learn new practice
• Master’s Degree (Computer Science, Engineering, Information Systems, Mathematics, Business Analytics, or relevant degree)

Knowledge:

• Demonstrated advanced knowledge of SQL, Java, Python, C/C++, Scala, Julia, and/or other modern data and analytics programming languages
• Demonstrated expertise in data modeling principles, data architecture, and database systems.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Knowledge of data architecture frameworks, distributed systems, and performance optimization at scale

Skills:

• Data solution design and architecture
• Coding
• Data Warehousing
• Database schema optimization
• Database Systems
• Technical leadership and mentoring
• Critical thinking skills
• Business communication
• ETL