Software Data Engineering Manager

About the Role

Our employees work on the world's most advanced software and electronics — from developing world-class autonomous mission management capabilities to advanced data analytics that support warfighters and the intelligence community. Spanning air, land, sea, and space, we develop the technology of tomorrow, delivered today. Drawing strength from our differences, we innovate for the future. Our flexible work environment gives you the opportunity to change the world without giving up your personal life. We put our customers first, exemplified by our mission: "We Protect Those Who Protect Us®."

Our engineers are the lifeblood of our company, and we're more than 5,000 strong. With robust educational and career-development opportunities, your potential to grow is limitless. The Digital Architecture Team (DAT) is seeking a highly experienced Software (Data) Engineering Manager to lead the team responsible for the lifecycle of engineering and operations data. The team designs and operates data pipelines, schemas, governance controls, databases, transformation workflows, and data-serving capabilities used by internal and external customers. This is a player-coach role. The manager will lead engineers, set technical direction, work with stakeholders, and remain involved in architecture, delivery, and production support. Our team has built a highly scalable, containerized gRPC microservices platform and micro-frontend web applications. You will help ensure that the data powering those systems is collected, transformed, secured, discoverable, reliable, and performant for our end customers.

Pursuant to a government contract, this position requires U.S. citizenship and eligibility for a future Secret clearance.

Responsibilities

• Lead, mentor, and develop a team of data engineers, data analytics engineers, and business intelligence engineers.
• Set the technical direction, roadmap, architecture, and delivery priorities for data pipelines, data schemas, Protobuf models, data governance automation, database administration, and data-platform operations.
• Design and maintain data pipelines for ingestion, transformation, validation, storage, and delivery.
• Develop data schemas, Protobuf models, and data contracts that support reliable data exchange across systems.
• Implement data transformation practices using dbt or comparable tools.
• Establish standards for testing, documentation, lineage, data quality, and reusable transformation models.
• Establish workflow orchestration practices using Dagster or comparable tools.
• Ensure workflows support scheduling, dependency management, retries, backfills, observability, and incident response.
• Apply Medallion architecture principles to organize raw, refined, curated, and serving data layers.
• Design and optimize data marts for analytical workloads, including complex calculations, aggregations, dashboards, reporting, and data visualization.
• Lead PostgreSQL administration and performance optimization, including query analysis, index design, schema design, partitioning, maintenance, backup and recovery, reliability, security, and capacity planning.
• Work with engineering, operations, security, and customer stakeholders to define requirements and deliver usable data solutions.
• Establish standards for data governance, lifecycle management, access controls, retention, lineage, and legacy-system retirement.
• Improve production reliability through monitoring, incident response, root-cause analysis, and preventive engineering work.
• Manage project plans, staffing, budgets, priorities, and resource allocation for the team's portfolio.
• Recruit, hire, onboard, and retain data engineering talent.
• Define and use measures for delivery, quality, reliability, and team performance.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related technical field.
• 8+ years of experience in software engineering, data engineering, platform engineering, or a related discipline.
• 3+ years of technical leadership experience as an engineering manager, technical lead, or team lead.
• Experience leading and developing software or data engineering teams.
• Experience delivering data platforms or data products that include data pipelines, data models, data governance, databases, and production operations.
• Experience with data transformation, data quality, lineage, governance, lifecycle management, and retirement or modernization of legacy data solutions.
• Strong SQL and PostgreSQL experience, including query tuning, execution-plan analysis, indexing, schema and data-model design, and database maintenance.
• Experience building data marts or analytical data models for aggregation-heavy reporting, dashboards, and visualization.
• Experience designing or operating data-serving patterns such as semantic layers, governed metrics, or comparable analytical consumption models.
• Experience with cloud technologies, Docker, Kubernetes, and CI/CD practices.
• Strong Python experience and familiarity with C#, Protobuf, and gRPC in a production software environment.
• Experience with GitLab, CI/CD pipelines, source control, and software configuration management.
• Experience conducting code reviews and applying engineering standards that improve code quality and maintainability.
• Experience supporting production systems, resolving incidents, and preventing recurring reliability issues.
• Ability to communicate technical decisions, risks, and tradeoffs to technical and non-technical stakeholders.
• Experience planning and delivering complex technical work across multiple teams or over multiple years.
• Strong problem-solving and analytical skills.
• Clear written and verbal communication and ability to present technical material to varied audiences.
• Ability to work effectively with engineering, operations, security, management, and customers.
• Ability to manage competing priorities in a fast-moving environment.
• Experience working in Agile or Scrum teams.
• Must be able to obtain a U.S. Secret Clearance.

Preferred Qualifications

• Hands-on experience with dbt, including testing, documentation, lineage, and modular transformation development.
• Hands-on experience with Dagster, including asset-based orchestration, scheduling, observability, and operational workflows.
• Experience implementing Medallion architecture patterns.
• Experience implementing semantic layers or governed metrics for analytics, business intelligence,