Data Engineer, Mid at Booz Allen in McLean, VA

Job description

Data Engineer, Mid The Opportunity: As a data engineer, you know that reliable data is critical to building modern applications and enabling informed decision-making. We’re looking for a data engineer like you to help develop and automate data pipelines that transform complex data into usable, reliable information. As a data engineer on our team, you’ll work with experienced engineers and technical teams to design, develop, test, and maintain data pipelines and data processing workflows. You’ll use modern data engineering technologies such as Databricks and Python to integrate, transform, and move data across enterprise environments. This is an opportunity to grow your data engineering expertise while working with cloud technologies, automation, and modern data platforms. You’ll collaborate with developers, data engineers, and stakeholders to solve technical challenges and deliver scalable solutions. Due to the nature of work performed within this facility, U.S. citizenship is required. What You’ll Work On: Develop and maintain data pipelines and automated data processing workflows. Build data transformations and processing workflows using Databricks, SQL, and Python. Integrate data from multiple sources and formats. Automate repetitive data processing and operational tasks. Test, troubleshoot, and optimize data pipelines for reliability and performance. Collaborate with senior engineers and technical teams to implement data solutions. Participate in Agile development, code reviews, testing, and deployment activities. Contribute to technical documentation and data engineering best practices. Work with us to use data for good. Join us. The world can’t wait. You Have: 3+ years of experience in data engineering, database development, or data warehousing Experience developing data pipelines using Python, and Apache Spark or PySpark for processing large datasets Experience with Git or GitHub for source-code management and collaborative development Experience with Jenkins, SQL, including complex queries, joins and aggregations, CTEs, window functions, query optimization, and performance tuning, and relational databases, including database development, troubleshooting, and performance considerations Knowledge of data warehousing concepts, including ETL/ELT, fact and dimension tables, star and snowflake schemas, slowly changing dimensions, and data integration, and data quality concepts, including data validation, completeness, accuracy, consistency, duplicate detection, and data reconciliation Knowledge of data modeling, including conceptual, logical, and physical data models, and data governance, including data ownership and stewardship, metadata, data lineage, data security, data classification, and data standards Knowledge of CI/CD pipelines, including automated builds, testing, and deployments Ability to develop and support Spark-based processing workflows Public Trust Bachelor's degree Nice If You Have: Experience with Databricks or similar cloud-based data platforms Experience with Amazon Web Services (AWS) Experience with AWS services such as S3, Glue, Lambda, or similar technologies Experience with data lake or Lakehouse environments Experience with DevSecOps practices, Infrastructure-as-Code, or automated data quality checks Experience working with large or complex datasets Experience working in federal or other highly regulated environments Ability to effectively use approved AI-assisted development tools such as GitHub Copilot, ChatGPT, Amazon Q, or similar tools, to improve productivity, troubleshoot issues, generate and review code, create documentation, and accelerate learning while following organizational security and data-protection standards Vetting: Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client; Public Trust determination is required. Compensation At Booz Allen, we celebrate your contributions, provide you with opportuni