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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Leidos, Inc. - **Location:** Gaithersburg, MD, United States - **Experience:** Expert - **Salary:** $131,300.0 - $237,350.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Geographic Information Systems, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Apache HTTP Server, Systems Engineering, Big Data, Cloud Computing, Cloud Engineering, Databases, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Security, Relational Databases, Geospatial Intelligence, Python (Programming Language), PostgreSQL, Meta-Data Management, Metadata Repositories, Operational Databases, Query Optimization, Cloud Services, SQL Databases, Data Streaming, Systems Integration, Transaction Data, Data Storage Technologies, Snowflake, Apache Spark, Indexer, Git, Data Lakes, Kubernetes, Infrastructure Automation Frameworks, Apache Flink, AWS Glue, AWS Fargate, Apache Kafka, Presto, Docker, Amazon Redshift, Databricks - **Published:** October 2, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9210192/senior-data-engineer ## About the Role Active Top Secret/SCI with the ability to successfully pass a Polygraph examination., * US citizenship is required per contract. * 12+ years of relevant software, data engineering, or data architecture experience, with demonstrated progression into senior technical or architecture responsibilities. * Expert-level experience designing and implementing large-scale data architectures, lakehouses, or analytical data platforms. * Strong hands-on experience with SQL and Python. * Strong experience with PostgreSQL and/or Amazon Aurora PostgreSQL. * Experience with Amazon S3 and object-storage-based data architectures. * Hands-on experience with modern lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent. * Experience designing hybrid architecture spanning relational, columnar, object-storage, and distributed analytical systems. * Experience with distributed query engines such as Trino/Presto or equivalent technologies. * Experience building batch and/or streaming data pipelines using technologies such as Apache Kafka, Spark, Flink, Airflow, Dagster, dbt, or equivalent. * Strong understanding of data modeling, partitioning, indexing, cataloging, schema evolution, and query optimization. * Experience with Docker/containerized services and modern cloud-native architectures. * Experience with Infrastructure as Code and Git-based CI/CD. * Strong understanding of data security, access controls, governance, and protecting sensitive data., * Experience with AWS-managed data services, particularly S3, Aurora PostgreSQL, Redshift, ECS/Fargate, Lambda, and related services. * Experience with Kubernetes and container orchestration. * Experience with data catalogs and metadata platforms such as OpenMetadata, AWS Glue Data Catalog, or equivalent. * Experience working with geospatial, telemetry, operational, or other high-volume datasets. * Experience designing platforms supporting both interactive queries and large-scale analytical workloads. * Experience supporting production data platforms in classified, DoD, Intelligence Community, or other high-security environments. * Experience providing technical directions to multidisciplinary engineering teams. Key Technologies Critical: SQL, Python, PostgreSQL/Aurora PostgreSQL, Amazon S3, Apache Iceberg/lakehouse architecture, distributed analytical querying, Trino/Presto, data modeling, query optimization Strongly Desired: Redshift, Kafka, Spark, Airflow/Dagster/dbt, Docker, Kubernetes, AWS, Infrastructure as Code, Git-based CI/CD Nice to Have: OpenMetadata/Glue Data Catalog, Flink, Databricks/Delta Lake, Snowflake, geospatial data experience #NSBA ## Description Join Leidos and help shape the future of geospatial intelligence! We are seeking an experienced and innovative Senior Systems Engineer to support the Maru Program with our Intelligence Community customer. If you're passionate about solving complex technical challenges, thrive in a fast-paced Agile environment, and enjoy collaborating with high-performing teams to deliver mission-critical capabilities, this is your opportunity to make a direct impact on national security., The Senior Data Engineer will lead the design and implementation of a scalable, cloud-native data architecture supporting large-scale operational and analytical workloads. This role will provide technical leadership for the development of hybrid analytical query capability, integrating relational databases, object storage, lakehouse technologies, and distributed query engines. The ideal candidate has deep hands-on experience designing modern data platforms and can make architecture decisions around data storage, ingestion, modeling, partitioning, cataloging, governance, and query performance., * Lead the architecture and implementation of a hybrid analytical query platform supporting large-scale operational and analytical data. * Design and implement modern data lakehouse architectures using object storage, relational databases, and distributed analytical technologies. * Develop scalable batch and streaming data pipelines for ingestion, transformation, enrichment, and delivery of data. * Design data models, partitioning strategies, indexing approaches, catalogs, and query architectures optimized for large datasets. * Integrate PostgreSQL/Aurora transactional data with analytical and object-storage platforms. * Design and optimize distributed query capabilities using technologies such as Trino/Presto or equivalent. * Develop solutions using Amazon S3, Apache Iceberg, Redshift, and other modern cloud data services. * Support data governance, metadata management, lineage, access controls, and security requirements. * Design and deploy containerized data services within cloud-native environments. * Provide technical leadership, architecture guidance, design reviews, and mentoring engineers to implementing the data platform. * Troubleshoot complex data, database, query-performance, infrastructure, and integration issues.