Senior Data Engineer

Leidos; Gaithersburg (MD); On-site; USD 131,000 - 237,000; Full time

Benefits offered by this job

Competitive compensation

Health and Wellness programs

Income Protection

Paid Leave

Retirement

Job summary

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 workloads within the Maru Program. You will guide data lakehouse architectures, batch/streaming pipelines, and distributed query engines, while ensuring data governance in a highly secure environment.

You will collaborate across teams to design and optimize data models, catalogs, and query architectures, leveraging Trino/Presto, S3, Iceberg,

Qualifications

• US citizenship is required per contract.
• 12+ years of relevant software, data engineering, or data architecture experience with progression into senior roles.
• 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 lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, Redshift, or equivalent.
• Experience with Trino/Presto or equivalent.
• Experience building batch and/or streaming data pipelines using Kafka, Spark, Flink, Airflow, Dagster, dbt, or equivalent.
• Docker and containerized services; IaC and Git-based CI/CD.
• Strong understanding of data security, governance, and protecting sensitive data.

Responsibilities

• Lead the architecture and implementation of a hybrid analytical query platform for large-scale data.
• Design modern data lakehouse architectures using object storage, relational databases, and distributed analytics.
• Develop scalable batch and streaming data pipelines for ingestion, transformation, and delivery.
• Model data schemas, partitioning, indexing, catalogs, and query architectures for large datasets.
• Integrate PostgreSQL/Aurora transactional data with analytical/object-storage platforms.
• Develop distributed query capabilities with Trino/Presto or equivalent.
• Build solutions using Amazon S3, Iceberg, Redshift and other cloud data services.
• Support data governance, metadata management, lineage, and access controls.
• Deploy containerized data services in cloud-native environments.
• Provide technical leadership, architecture reviews, and mentoring to engineers.
• Troubleshoot data, database, performance, and integration issues.

Skills

SQL

Python

PostgreSQL

Amazon Aurora PostgreSQL

Amazon S3

Apache Iceberg

Redshift

Trino/Presto

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

Tools

OpenMetadata

AWS Glue Data Catalog

Kubernetes

ECS/Fargate

Lambda

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.