Senior Data Engineer

Our Ideal CandidateWe are looking for a Senior Data Engineer who is a self-starter and detail-oriented with a strong blend of technical expertise and business acumen. The ideal candidate has a strong foundation in data engineering, experience working with healthcare data, and the ability to build scalable data-driven solutions. You are a proactive problem-solver who takes ownership of your work, continuously seeks to improve data quality and accessibility, and is committed to delivering high-quality data solutions.ResponsibilitiesLead data modeling efforts to create optimized data structures for reporting and analytical purposes.Design, develop, and maintain end-to-end data pipelines that transform raw source data into high-quality, actionable datasets.Build the company's data infrastructure and data catalog, from data ingestion through the semantic layer, ensuring a robust, scalable architecture on AWS. Collaborate with cross-functional teams (product, technology, operations, etc.) to understand data needs, align them with business goals, and translate them into technical solutions. QualificationsBachelor's or Master's (preferred) degree in Computer Science, Engineering, or a related quantitative field (Data Science).5+ years of experience as a Data Engineer, Analytics Engineer, or similar role, with a strong focus on the development of end-to-end data solutions and products.5+ years of hands-on experience with AWS cloud technologies is required, including designing, building, and maintaining cloud-based data infrastructure and infrastructure as a Code (IaC), such as CDK or Terraform. Proficiency in building and managing data infrastructure and ETL pipelines within AWS, leveraging services like AWS Glue, Athena, Redshift, Aurora, RDS, DynamoDB, EMR, Lambda, IAM, S3, EC2, CLI. Demonstrated experience in designing and implementing robust data models for analytical purposes.Strong proficiency in SQL and experience with various database systems (e.g., MySQL, NoSQL, Snowflake, Vector Databases).Strong proficiency in Python for data engineering and analytics, and extensive experience with data pipeline development and orchestration tools (e.g., Airflow, dbt).Experience with Power BI or Tableau for data reporting and dashboard development.Experience shipping data products to production and understanding software development lifecycle best practices.Strong problem-solving skills, the ability to work independently, and good communication and collaboration skills. Ability to learn new technologies and adapt to a fast-paced environment. Awareness of HIPAA, PHI, and other healthcare-specific regulations related to data and AI.