Data Engineer - AWS/Databricks

Responsibilities

• 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.

Qualifications

• 2+ years of experience in data engineering and Agile analytics
• 2+ years of experience creating software for retrieving, parsing and processing structured and unstructured data
• 1 to 2 years of experience building scalable ETL and ELT workflows for reporting and analytics
• 1 or more 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

About Acuity

At Acuity, your work matters—and so does your experience. We’re a management and technology consulting firm supporting critical federal missions, where you’ll have the opportunity to solve meaningful challenges, work alongside high-performing teams, and make a real impact from day one.