Data Platform Engineer

• Design and maintain scalable, cloud-native data platforms, including data lakes, lake houses, and data warehouses (e.g., AWS, Azure, GCP).

Self-Service Enablement:

• Build reusable CI/CD templates and Infrastructure as Code to allow data scientists and analysts to provision environments and build pipelines independently.

• Develop robust ETL and ELT frameworks for both batch and streaming data. Implement strict role-based access controls, data encryption, data lineage tracking, and compliance frameworks to protect sensitive digital health or enterprise data.

• Monitor platform performance, storage use, and query responsiveness to ensure high availability and cost efficiency. Collaborate with Data Architects, Software Developers, and Data Scientists to integrate RESTful APIs and deliver cohesive end-to-end data products.

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• Minimum 4 years in data engineering, platform engineering, or a highly technical DevOps or data role.
• Proficiency in Python, Java, or Scala; advanced SQL skills; and experience with NoSQL and distributed database systems.
• Hands-on experience with data lake and warehouse technologies such as Databricks, Snowflake, Apache Spark, or Apache Kafka.
• Familiarity with containerization tools (Docker, Kubernetes), workflow orchestration platforms (Airflow, Dagster), and Infrastructure as Code tools (Terraform).
• Must have a TS/SCI Security clearance

• Covers 100% of employee benefit premiums, including Medical (PPO or HDHP Option), Vision, Dental
• Matching 401K
• Short- and Long-Term Disability
• Pet Insurance
• Professional Development/Education Reimbursement
• Parking and Transit Benefits for NY, NJ, ATL, and DC Metro areas