Junior Data Engineer

Overview BigBear.ai•Norfolk, VA

About The Position

BigBear.ai is seeking a motivated and detail-oriented Junior Data Engineer to join its Data Architecture & Engineering team. The role supports development and maintenance of data pipelines, database integrations, and data quality processes that transform raw data into reliable, accessible, and actionable information. The engineer will work with SQL databases, ETL processes, cloud platforms, and reporting tools to support mission-critical applications, analytics, and enterprise data initiatives. The role offers an opportunity to develop technical skills while contributing to government and national security missions, collaborating with experienced engineers, analysts, and technical stakeholders to improve data reliability, streamline processing, document data assets, and support secure and efficient operations.

Requirements

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 ability to investigate and resolve data discrepancies.
Ability to document technical processes, communicate findings clearly, and collaborate with technical and nontechnical stakeholders.
Ability to work in a team environment, learn new tools and technologies, and support multiple data-related priorities.

Nice To Haves

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.

Responsibilities

Assist in developing, maintaining, and improving 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 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.
Support metadata and data inventory organization and management to improve data governance, traceability, and standardization.
Assist in developing and maintaining reports, dashboards, and data products for technical teams and leadership.
Support secure data access and handling, including user permissions, access controls, and 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.