AWS Data Engineer

AWS Data Engineer

• Remote
• Rate - $65/hr on C2C

Required Skills &

Qualifications:

• Strong experience with AWS data and serverless services (Lambda, Glue, Athena, S3, Step Functions or similar orchestration tools).
• Advanced proficiency in Python (required) and SQL, with experience in relational and No
  
  SQL databases and in building reusable ETL/ELT libraries. Hands-on experience with PySpark for distributed data processing is strongly preferred;
  Type Script experience for AWS CDK required.
• Experience with MLOps practices, including versioned feature and training datasets, orchestration of training and scoring workflows, CI/CD, model/data monitoring, and reproducible deployments in partnership with AI.
• Solid understanding of data modeling principles for AI workloads. Apply schema evolution, incremental processing, partitioning, and columnar or open-table formats such as Parquet and Iceberg.
• Experience designing and operating data pipelines at scale, including batch and near real time ingestion. Hands-on experience with Kafka is preferred.
• Familiarity with SQL and query optimization in columnar data stores and engines.
• Knowledge of data quality, governance, and security for sensitive healthcare and financial data, including least-privilege access, retention, classification, tokenization, and de-identification.
• Hands on experience with Infrastructure as Code, preferably AWS CDK, for provisioning and managing data infrastructure.
• Ability to partner with AI and Analytics teams to design data solutions for model experimentation and production;
  Kedro or similar workflow experience is a plus.
• Knowledge of responsible AI and data-use practices, including permitted-use controls, privacy, fairness considerations, documentation, and governance for sensitive healthcare and financial data.
• Strong communication skills to explain complex data concepts clearly to business stakeholders; regulated-domain experience, preferably healthcare claims or insurance, is a plus.

Minimum Requirements:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related field, or equivalent practical experience; a master's degree is preferred.
• 5+ years in data engineering or a related role, with significant ownership of production data pipelines and analytics platforms; hands-on ML/AI experience supporting feature preparation, model training, deployment, or monitoring is strongly preferred.
• Experience with AWS data services in a production environment (for example, Lambda, Glue, Athena, and S3) is preferred; equivalent production experience on another cloud data platform will be considered.
• Experience building and maintaining data solutions that support reporting, BI, and/or AI/ML initiatives.