Data Engineer - AWS/Databricks - Mid Level

• Build and maintain scalable PySpark-based data pipelines in Databricks notebooks to support ingestion, transformation, and enrichment of structured and semi-structured data.

• Design and implement Delta Lake tables optimized for ACID compliance, partition pruning, schema enforcement, and query performance across large datasets.

• Develop ETL and ELT workflows that integrate multiple source systems into a centralized, query-optimized data warehouse architecture.

• Leverage Spark SQL and DataFrame APIs to implement business rules, dimensional joins, and aggregation logic aligned to warehouse modeling best practices.

• Collaborate with data architects and engineers to implement cloud-native data solutions on AWS using S3, Glue, RDS, and IAM for secure, scalable storage and access control.

• Optimize pipeline performance through intelligent partitioning, caching, broadcast joins, and adaptive query tuning.

• Deploy and version data engineering assets using Git-integrated development workflows and automate deployment with CI/CD tools such as GitLab or Jenkins.

• Monitor pipeline health, job execution, and cluster utilization using native Databricks tools and AWS CloudWatch, identifying bottlenecks and optimizing cost-performance tradeoffs.

• Conduct technical discovery and mapping of legacy source systems, identifying required transformations and designing end-to-end data flows.

• Implement governance practices including metadata tagging, data quality validation, audit logging, and lineage tracking using platform-native features and custom logic.

• Support ad hoc data access requests, develop reusable data assets, and maintain shared notebooks that meet operational reporting and analytics needs across teams.

• 4+ years of experience in data engineering and Agile analytics
• 4+ years of experience creating software for retrieving, parsing and processing structured and unstructured data
• 2+ years of experience building scalable ETL and ELT workflows for reporting and analytics
• 2 + years experience building enterprise data engineering solutions in the cloud, with preferred experience with cloud native technologies from AWS and Databricks
• Experience with data quality, validation frameworks, and storage optimization strategies
• BA or BS degree

Clearance Requirement:

• Must be US Citizen with an ability to obtain and maintain US Suitability