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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Junior Data Engineer - **Company:** BigBear.ai, Inc. - **Location:** Norfolk, VA, United States - **Experience:** Starter - **Contract:** Permanent contract - **Skills:** Query Performance, Agile Methodology, Amazon Web Services, Data Analysis, Cloud Computing, Information Systems, Databases, Data Architecture, Data Validation, Data Dictionary, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Security, Relational Databases, Database Development, Database Storage Structures, Document-Oriented Databases, File Transfer, Data Flow Control, Identity and Access Management, Python (Programming Language), Metadata, Meta-Data Management, Microsoft SQL Server, Query Optimization, Power BI, Standard Sql, DataOps, SQL Databases, SQL Server Reporting Services, Systems Integration, Tableau (Software), Enterprise Data Management, Data Processing, Scripting, Enterprise Software Applications, Cloud Platform System, Information Technology, Data Analytics, Performance Monitor, Data Management, Tools for Reporting, Data Pipelines, Databricks - **Published:** October 28, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88736426/1 ## About the Role BigBear.ai is seeking a motivated and detail-oriented Junior Data Engineer to join our Data Architecture & Engineering team. In this role, you will support the development and maintenance of data pipelines, database integrations, and data quality processes that transform raw data into reliable, accessible, and actionable information., * Must be eligible to obtain and maintain a Secret security clearance. * Bachelor's degree in Computer Science, Information Systems, Engineering, Data Analytics, Accounting, or a related field, or equivalent relevant professional experience. * 3-5 years of relevant experience in data analysis, data engineering, database support, ETL development, reporting, or data integration. * Working knowledge of SQL and relational databases, including the ability to write queries and retrieve, manipulate, and validate data. * Familiarity with data imports, ETL processes, data transformations, or integrations between multiple source systems. * Experience performing data validation, quality assurance, auditing, reconciliation, or other activities that improve data accuracy and reliability. * Basic understanding of database structures, data relationships, query performance, and data management principles. * Strong analytical and problem-solving skills, attention to detail, and the ability to investigate and resolve data discrepancies. * Ability to document technical processes, communicate findings clearly, and collaborate with both technical and nontechnical stakeholders. * Ability to work in a team environment, learn new tools and technologies, and support multiple data-related priorities. What we'd like you to have * Exposure to AWS, Databricks, or other cloud-based data platforms. * Experience with Microsoft SQL Server, Databricks, or other relational database technologies. * Familiarity with data governance, metadata management, data inventories, data dictionaries, or data cataloging. * Experience with Power BI, Tableau, SQL Server Reporting Services (SSRS), or other reporting and visualization tools. * Familiarity with Python, R, or scripting used to support data processing and automation. * Experience integrating data across enterprise applications, databases, file transfers, or external data sources. * Understanding of data security, access management, regulatory compliance, or handling sensitive information. * Exposure to Agile software development, IT service management, or collaborative development environments. * Interest in supporting government, defense, critical infrastructure, or other mission-focused data environments. ## Description You will work with SQL databases, ETL processes, cloud platforms, and reporting tools to support mission-critical applications, analytics, and enterprise data initiatives. This position is ideal for someone with a strong foundation in SQL, data integration, database management, and data validation who is looking to grow their technical skills while contributing to meaningful government and national security missions. The successful candidate will collaborate with experienced engineers, analysts, and other technical stakeholders to improve data reliability, streamline data processing, document data assets, and support secure and efficient data operations. What you will do * Assist in developing, maintaining, and improving data pipelines and ETL processes to ingest, transform, validate, and deliver data from multiple source systems. * Write, maintain, and optimize SQL queries to retrieve, transform, validate, and analyze data across relational databases. * Support data integration efforts by connecting source systems, developing data imports, and helping automate recurring data transfers and reporting processes. * Perform data quality checks, audits, and reconciliations to identify inconsistencies, improve accuracy, and maintain data integrity. * Assist with database development and maintenance, including schema documentation, query optimization, data organization, and performance monitoring. * Support cloud-based data engineering and integration activities using AWS, Databricks, and other approved enterprise data platforms. * Develop and maintain data dictionaries, technical documentation, dataflow diagrams, and standard operating procedures to improve data discoverability and usability. * Support the organization and management of metadata and data inventories to improve data governance, traceability, and standardization across systems. * Assist in developing and maintaining reports, dashboards, and data products that provide actionable information to technical teams and leadership. * Support secure data access and handling practices, including user permissions, access controls, and the protection of sensitive information. * Collaborate with software developers, data analysts, and cross-functional teams to troubleshoot data issues and deliver incremental improvements using Agile development practices. * Contribute to process automation and continuous improvement initiatives that reduce manual effort, improve data processing efficiency, and increase confidence in enterprise data.