Site Reliability Data Engineer

Leidos is seeking a Site Reliability Data Engineer to support the SMIT program for the Navy. The role focuses on building and operating secure enterprise data solutions along with automated testing frameworks that validate resilience, performance, and failure scenarios. You will work across hybrid cloud and on-premises environments and help meet SLOs for mission-critical services.

What you’ll do

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines that collect, transform, validate, and deliver structured and unstructured data from enterprise systems, applications, APIs, logs, files, and databases.
• Build and optimize data models, schemas, tables, views, and curated datasets to support analytics, business intelligence, operational reporting, and downstream application needs.
• Develop data-processing solutions using SQL, Python, and other approved technologies, applying reusable engineering patterns, source control, peer review, and documented release practices.
• Integrate cloud and on-premises data platforms while supporting secure data movement, interoperability, availability, retention, and performance across hybrid enterprise environments.
• Implement automated data-quality checks, reconciliation controls, monitoring, alerting, and exception handling to identify incomplete, inaccurate, duplicated, delayed, or failed data flows.
• Troubleshoot pipeline failures, data discrepancies, performance degradation, access issues, and integration defects, performing root-cause analysis and corrective and preventive actions.
• Collaborate with analysts, business intelligence developers, data owners, system administrators, and mission stakeholders to define data requirements, source-to-target mappings, transformation rules, service expectations, and acceptance criteria.
• Apply data governance, security, privacy, least-privilege access, auditability, and records-retention requirements across the data lifecycle in coordination with cybersecurity and compliance teams.
• Support platform upgrades, data migrations, modernization efforts, capacity planning, and performance tuning while minimizing disruption to production services.
• Create and maintain technical documentation, including architecture diagrams, data dictionaries, lineage documentation, interface specifications, runbooks, standard operating procedures, and troubleshooting guides.
• Participate in Agile planning, backlog refinement, technical reviews, demonstrations, incident response, and after-hours support when required to sustain mission-critical services.
• Develop and execute tests focused on system resilience, performance underload, and failure scenarios.
• Work with other Site Reliability Engineers and development teams to create automated testing frameworks that simulate real-world conditions and validate system behavior under normal and stress conditions to ensure resilient services and alignment with established SLOs.
• Support the operations and maintenance of the enterprise network.

Required qualifications

• B.S. Degree and 4–8 years of prior relevant experience, or Master’s with 2–6 years of prior relevant experience in data engineering, computer science, information systems, software engineering, mathematics, or a related technical discipline (at least four years of relevant experience; additional directly related experience may be considered in place of a degree).
• U.S. citizenship and an active DoD Secret Security Clearance.
• Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
• Must be located in (or able to work onsite at Navy Base as required) San Diego, California; the Hampton Roads, Virginia area; or Jacksonville, FL.
• At least three years of hands-on experience developing, operating, or supporting production data pipelines, data integrations, data warehouses, data lakes, or comparable enterprise data solutions.
• Proficiency with SQL and at least one general-purpose scripting/programming language such as Python for data extraction, transformation, validation, automation, and troubleshooting.
• Experience with ETL/ELT, relational data structures, data modeling, schema design, source-to-target mapping, data quality, metadata, and lifecycle management.
• Experience integrating data from multiple source types including relational databases, APIs, flat files, application data, system logs, or message-based interfaces.
• Working knowledge of cloud and on-premises infrastructure concepts including authentication and authorization, network connectivity, encryption, secure file transfer, and service accounts as they relate to data engineering.
• Ability to diagnose production data issues, analyze logs and metrics, resolve failed jobs or performance problems, and document root cause and corrective action.
• Capability to work independently and collaboratively in a high-tempo operational environment, manage competing priorities, communicate clearly, and produce complete technical documentation.
• Working knowledge of PowerShell, Python, and Ansible, with practical familiarity using LLMs and AI-enabled tools.

Technologies

SQL, Python, PowerShell, Ansible, LLMs, AI-enabled tools, ETL, ELT, Agile/DevOps

Benefits

• Competitive compensation
• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement

Nice to have

• Business intelligence experience including dashboards, reports, semantic models, KPIs, and self-service analytics solutions, with Microsoft Power BI and DAX knowledge highly desirable.
• Microsoft Certified: Azure Administrator Associate (AZ-104).
• Hands-on experience with Azure data and analytics services such as Azure Data Factory, Azure SQL, Azure Storage, Synapse Analytics, Databricks, or comparable cloud data platforms.
• Familiarity with STIGs, RMF, vulnerability management, system hardening, security controls, and applicable compliance frameworks.
• Experience with automation, configuration-management, source-control, or CI/CD tools such as Ansible, Jenkins, and Bitbucket.
• Experience designing or supporting data solutions in classified, DoD, federal government, or other highly regulated environments.
• Experience with modern data-platform concepts including data lakes, lake houses, dimensional modeling, streaming or event-driven data, distributed processing, or containerized workloads.
• Experience with data cataloging, lineage, master/reference data, role-based access controls, audit logging, backup/recovery, and disaster recovery practices.
• Relevant technical certifications in Azure, data engineering, database administration, analytics, cloud architecture, or security.
• Strong customer engagement, requirements analysis, technical presentation, mentoring, and cross-functional collaboration skills.
• Experience with graph databases such as Neo4j and query languages such as Cypher, including property graph modeling.
• Familiarity with knowledge graphs, ontologies, or semantic data models and controlled vocabularies.
• Experience with entity resolution/record linkage and reconciling conflicting values across multiple authoritative sources into a single trusted record.