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Job Description

Leidos is seeking a Senior Data Engineer to lead the design and implementation of a scalable, cloud-native hybrid analytical query platform for large-scale operational and analytical workloads within the Maru Program. The role involves technical leadership across data lakehouse architecture, batch and streaming pipelines, distributed query engines, and data governance in a highly secure environment.

Key Responsibilities

  • 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 to engineers implementing the data platform.
  • Troubleshoot complex data, database, query-performance, infrastructure, and integration issues.

Required Qualifications

  • 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 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 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, PostgreSQL/Aurora, 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.

Location

Gaithersburg, MD (onsite) is the program’s primary work location.

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 and Posting Details

Pay Range: USD 131,300 - 237,350 per yearly. Original Posting: October 1, 2026. Pay Range: $131,300.00 - $237,350.00.

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