Leidos is building a scalable, cloud-native hybrid analytical query platform for the Maru Program, supporting large-scale operational and analytical workloads in a highly secure environment. As a Senior Data Engineer in Gaithersburg, MD (onsite), you will help design and deliver a modern data lakehouse and distributed query foundation, with strong technical leadership and mentoring for engineers working across data architecture, pipelines, and governance.
Responsibilities
- Lead the architecture and implementation of a hybrid analytical query platform for large-scale operational and analytical data.
- Design and implement modern lakehouse architectures using object storage, relational databases, and distributed analytical technologies.
- Develop scalable batch and streaming pipelines for ingestion, transformation, enrichment, and delivery.
- Create 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 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 through architecture guidance, design reviews, and mentoring engineers.
- Troubleshoot complex data, database, query performance, infrastructure, and integration issues.
Requirements
- 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).
- Experience building batch and/or streaming data pipelines using 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 and 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.
Technologies
SQL, Python, PostgreSQL, Amazon Aurora PostgreSQL, Amazon S3, Apache Iceberg, Redshift, Trino/Presto, object storage, relational databases, lakehouse technologies, Apache Kafka, Spark, Flink, Airflow, Dagster, dbt, Docker, Infrastructure as Code, Git-based CI/CD, Databricks/Delta Lake, Snowflake, OpenMetadata, AWS Glue Data Catalog, Kubernetes, ECS/Fargate, Lambda.
Benefits
- Competitive compensation
- Health and Wellness programs
- Income Protection
- Paid Leave
- Retirement
Security Clearance
Active Top Secret/SCI with the ability to successfully pass a Polygraph examination.
Preferred Qualifications
- 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.
Compensation: USD 131,300 - 237,350 per yearly (Pay Range $131,300.00 - $237,350.00).
Original Posting: October 1, 2026
