28 days ago
Base Salary
$131k - $237k/yr
Responsibilities
- Lead architecture and implementation of a hybrid analytical query platform for large-scale operational and analytical data.
- Design data lakehouse architectures using relational databases, object storage, and distributed analytical technologies.
- Build scalable batch and streaming pipelines for data ingestion, transformation, enrichment, and delivery.
- Design data models, partitioning, indexing, 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 technologies.
- Develop solutions using Amazon S3, Apache Iceberg, Redshift, and related cloud data services.
- Support data governance, metadata management, lineage, access controls, and sensitive-data security requirements.
- Design and deploy containerized data services in cloud-native environments.
- Provide technical leadership, architecture guidance, design reviews, and mentoring to engineering teams.
- Troubleshoot complex data, database, query-performance, infrastructure, and integration issues.
Requirements
- 12+ years of relevant software, data engineering, or data architecture experience with 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.
- Experience with lakehouse technologies such as Apache Iceberg, Databricks/Delta Lake, Snowflake, or Redshift.
- Experience designing hybrid architectures across relational, columnar, object-storage, and distributed analytical systems.
- Experience with distributed query engines such as Trino/Presto.
- Experience building batch or streaming pipelines using technologies such as Kafka, Spark, Flink, Airflow, Dagster, or dbt.
- Strong understanding of data modeling, partitioning, indexing, cataloging, schema evolution, and query optimization.
- Experience with Docker/containerized services and cloud-native architectures.
- Experience with Infrastructure as Code and Git-based CI/CD.
- Strong understanding of data security, access controls, governance, and sensitive-data protection.
- U.S. citizenship is required per contract.
- Active Top Secret/SCI clearance and ability to successfully pass a polygraph examination are required.
- Preferred qualifications include AWS-managed data services, Kubernetes, OpenMetadata, AWS Glue Data Catalog, high-volume or geospatial datasets, classified or DoD environments, and providing technical direction to multidisciplinary teams.
Benefits
- Primary work location is Gaithersburg, Maryland.
- This is a U.S. position supporting a classified Intelligence Community customer.
- The posting anticipates the requisition will remain open for at least 3 days from the October 1, 2026 original posting date.
- Pay range is $131,300.00-$237,350.00.
Tech Stack
Amazon RedshiftApache AirflowApache FlinkApache KafkaApache SparkAWSDatabricksdbtDockerGitKubernetesPostgreSQLPrestoPythonSnowflakeSQL
Categories
Data Engineering
About Leidos
Leidos builds and operates technology and engineering solutions for defense, intelligence, civil, and health agencies, including systems integration, cyber, enterprise IT, sensors, and healthcare IT. It primarily sells through government contracts and long-term programs, plus managed services and mission software. Founded in 1969 and headquartered in Reston, Virginia, Leidos is a Fortune 500 public company on the NYSE; customers include U.S. defense and intelligence agencies and civil bodies such as the FAA.