Senior Data Engineer

We 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.

• Lead 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.

• Bachelor'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, Dynamo
  
  DB, 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, No
  
  SQL, 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.