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

Senior Data Engineer