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Strong employer brand, generalist data engineer title, metro location, and broad multi-stack requirements.
Core data engineering skills transfer across industries, though enterprise systems and life-sciences domain add some bias.
Explicit 6+ years plus mandatory Databricks/Spark, Python, AWS, and API requirements drive high strictness.
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Design, build, and support API-driven data ingestion and delivery pipelines, data lakes, and data warehouses across on-premises and cloud environments.
Build and maintain API integrations using AWS Lambda, API Gateway, and REST/SOAP protocols, including Salesforce and Oracle system interfaces.
Optimize SQL queries and support data quality, integrity, and troubleshooting for large, complex datasets and integration workflows.
Bachelor’s degree in Computer Science or related field (or equivalent experience).
6+ years of experience in data engineering and REST API development.
Experience with Databricks or Spark-based platforms and Python (including PySpark).
Proficient in AWS services (S3, Athena, Redshift, API Gateway, Lambda, etc.), SQL performance tuning, and CI/CD tools including Git and Terraform.
Experienced in developing RESTful APIs using microservices architecture with strong knowledge of API security standards such as OAuth2.
Skilled in integrating enterprise systems (Salesforce, Oracle, SAP) and handling complex data engineering tasks in hybrid cloud environments.
Comfortable working with containerization (Docker, Kubernetes), event-driven architectures, and infrastructure as code tooling for scalable deployments.