Senior Data Engineer

Acuity•Reston, VA

About The Position

Acuity, Inc. seeks a Senior Data Engineer to lead the design, development, and optimization of modern data pipelines and analytics solutions supporting a federal client. This role builds and maintains robust data integration, ETL/ELT, and analytic processing capabilities across the data warehouse, data lake, and analytics platform environment. The Senior Data Engineer provides hands-on technical leadership across data engineering, platform design, and advanced analytics enablement. This individual drives data quality, performance, scalability, security, and operational reliability while supporting adoption of new data technologies and delivery of Big Data, Advanced Analytics, and Machine Learning solutions. Why Acuity? We’re building more than careers—we’re building a place people genuinely love to work. At Acuity, you’ll get: Strong work-life balance and a people-first culture Competitive compensation + Health/Dental/Vision coverage 401(k) with company match Up to $6,000/year for training & professional development 🏆 Recognized as a Best Places to Work (Washington Business Journal, 8+ years) 🏆 Named a Top Workplace by The Washington Post (2022–2025) Ready to grow with a team that invests in you? Learn more: www.myacuity.com Are you ready to use your expertise in the areas of IT Modernization, Data Enablement, and Hyperautomation to make a real difference? Join Acuity, Inc., a technology consulting firm that supports federal agencies. We combine industry partnerships and long-term federal experience with innovative technical leadership to support our customers’ critical missions.

Requirements

Bachelor’s degree in Computer Science , Engineering, or a related field
8+ years of experience developing and coding software or data engineering solutions
Strong hands-on experience with Databricks and cloud-based data technologies
Strong experience building and maintaining large-scale ETL/ELT pipelines and data integration solutions
Experience supporting data warehouse, data lake, and analytics platform architectures
Strong programming skills in Python, Scala, SQL , or similar data engineering languages
Experience optimizing data workflows for performance, reliability, and scalability
Experience implementing data quality, security, and operational controls in production environments
Ability to support advanced analytics and machine learning delivery from a data engineering perspective
Strong problem-solving skills and ability to work effectively across cross-functional technical teams
Must be a U.S. Citizen with the ability to obtain and maintain U.S. suitability

Nice To Haves

Experience with distributed data processing frameworks such as Apache Spark
Experience supporting Big Data and Advanced Analytics platforms in cloud environments
Experience enabling or supporting Machine Learning workflows and feature or training data pipelines
Experience with CI/CD, automation, and deployment practices for data platforms
Experience with cloud-native data services in AWS or similar environments
Experience mentoring engineers and establishing engineering standards
AWS Certified Machine Learning – Specialty
Data Science Council of America (DASCA) certifications
Databricks Certified Machine Learning Associate
Databricks Certified Developer for Apache Spark
Databricks Certified Data Engineer Associate
Databricks Certified Data Engineer Professional
AWS Certified Data Analytics – Specialty
Python or Scala programming certification

Responsibilities

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration solutions
Build and optimize data workflows across data warehouse, data lake, and analytics platforms
Lead ingestion, transformation, curation, and delivery of structured, semi-structured, and unstructured data
Implement data quality checks, validation rules, and monitoring across pipelines and datasets
Improve performance, scalability, reliability, and security of data processing solutions
Develop reusable engineering patterns, frameworks, and best practices
Support cloud-based data platform development, with strong emphasis on Databricks and related cloud services
Collaborate with engineers, analysts, architects, and stakeholders to translate requirements into technical solutions
Support design and delivery of Big Data, Advanced Analytics, and Machine Learning use cases
Provide technical leadership through code reviews, troubleshooting, standards development, and mentoring
Evaluate and apply new data technologies that improve capability, efficiency, or maintainability
Maintain technical documentation for pipelines, transformations, data flows, and engineering standards