Data Engineer - AWS/Databricks - Mid Level

Acuity, Inc. is a management and technology consulting firm supporting critical federal missions, seeking a skilled Data Engineer to join their Engineering Team. The role involves designing and delivering AWS cloud-scale data platforms, building scalable data pipelines, and collaborating with data architects to implement cloud-native data solutions.

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

Skills

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

Benefits

• Personalized development plans
• Mentorship
• Up to $3,000 annually for training and certifications
• Up to $3,000 for degree seeking programs
• Competitive compensation
• Comprehensive benefits
• A strong focus on work-life balance
• Work remotely (#LI-Remote)

Company Overview