Data Engineer, Senior at Booz Allen in McLean, VA

Job description

Data Engineer, Senior The Opportunity: As a data engineer, you know that well-designed data pipelines are the foundation for turning complex data into actionable insights. We’re looking for a data engineer like you to help build and modernize scalable data solutions that support mission-critical applications and analytics. As a data engineer on our team, you’ll design, develop, and maintain data pipelines and automated data workflows using modern cloud and data engineering technologies. You’ll work across technical teams to integrate data from multiple sources, transform and optimize datasets, and deliver reliable data products that support business and mission needs. You’ll have the opportunity to work with technologies such as Databricks and AWS, while applying modern engineering practices to automate and streamline data delivery. You’ll collaborate with data engineers, sof tware developers, architects, and client stakeholders to solve complex data challenges and continuously improve the platform. Due to the nature of work performed within this facility, U.S. citizen ship is required . What You’ll Work On: Design, develop, test, and maintain scalable data pipelines and data processing workflows. Build data solutions using Databricks, including data transformation, processing, and orchestration. Develop automated workflows to improve the reliability, efficiency, and repeatability of data processing. Integrate data from multiple sources and formats into enterprise data platforms. Develop and optimize data transformations using SQL and Python. Troubleshoot data pipeline issues and identify opportunities for performance and reliability improvements. Collaborate with sof tware developers, data engineers, architects, and stakeholders to comprehend requirements and deliver technical solutions. Apply Agile development practices, version control, testing, and CI / CD throughout the sof tware development lifecycle. Work with us to use data for good. Join us. The world can’t wait. You Have: 5+ years of experience in data engineering, database development, or data warehousing Experience with SQL, including complex queries, joins and aggregations, CTEs, window functions, query optimization, and performance tuning, and relational databases, including database development, troubleshooting, and performance tuning Experience developing and maintaining data pipelines using Python, and Apache Spark or PySpark for processing and transforming large datasets, including performance optimization and troubleshooting Experience with data engineering platforms such as Databricks Experience with Amazon Web Services ( AWS ) and AWS data services such as S3, EMR, Glue, Lambda, or NoSQL databases Experience with CI / CD pipelines, including using platforms such as GitHub Actions, including automated builds, testing, deployment, and promotion across environments Knowledge of database design principles, and data warehousing concepts, including ETL / ELT, fact and dimension tables, star and snowflake schemas, slowly changing dimensions, data integration, and incremental data processing Ability to independently troubleshoot data pipeline failures, data issues, performance problems, and production incidents, and identify appropriate root causes and corrective actions Public Trust Bachelor's degree in CS Nice If You Have: Experience with data lake or Lakehouse architectures Experience with DevSecOps practices Experience working in federal or other highly regulated environments Knowledge of data modeling, including conceptual, logical, and physical data models, dimensional modeling, and designing models to support analytics and reporting requirements Ability to contribute to technical design and architecture discussions, evaluate implementation approaches, and develop scalable, maintainable, and reliable data engineering solutions Ability to effectively use AI-assisted development tools for development productivity, code generation and review, troubleshooting, S