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 and automated testing frameworks that help validate resilience, performance, and failure scenarios across hybrid cloud and on-prem environments while meeting service level objectives (SLOs).

Responsibilities

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines to 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 data sets for 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, supporting secure data movement, interoperability, availability, retention, and performance in hybrid enterprise environments.
• Implement automated data-quality checks and reconciliation controls, including monitoring, alerting, and exception handling for incomplete, inaccurate, duplicated, delayed, or failed data flows.
• Troubleshoot pipeline failures, data discrepancies, performance degradation, access issues, and integration defects; conduct root-cause analysis and implement corrective and preventive actions.
• Partner 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 and security practices across the data lifecycle, including privacy, least-privilege access, auditability, and records-retention requirements in coordination with cybersecurity and compliance teams.
• Support platform upgrades, data migrations, modernization initiatives, capacity planning, and performance tuning while minimizing disruption to production services.
• Create and maintain technical documentation such as 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 activities when required to sustain mission-critical services.
• Develop and execute resilience-focused tests, including 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.
• Support the operations and maintenance of the enterprise network.

Requirements

• Requires a 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, with at least four years of relevant experience; additional directly related experience may be considered in place of a degree.
• Must be a U.S. citizen and possess 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, integrations, data warehouses, data lakes, or comparable enterprise data solutions.
• Demonstrated proficiency with SQL and at least one general-purpose scripting or programming language such as Python, for extraction, transformation, validation, automation, and troubleshooting.
• Experience with ETL/ELT concepts, 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, authentication and authorization, network connectivity, encryption, secure file transfer, and service accounts as they relate to data engineering.
• Experience diagnosing production data issues, analyzing logs and metrics, resolving failed jobs or performance problems, and documenting root cause and corrective action.
• Ability to work independently and collaboratively in a high-tempo operational environment, manage competing priorities, communicate technical information clearly, and produce complete technical documentation.
• Working knowledge of PowerShell, Python, and Ansible, with practical familiarity using large language models (LLMs) and AI-enabled tools.

Technologies

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

Nice to Have

• Business intelligence experience, including development or support of dashboards, reports, semantic models, KPIs, and self-service analytics solutions, with Microsoft Power BI (and associated 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, the Risk Management Framework (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 implementing data cataloging, lineage, master or reference data, role-based access controls, audit logging, backup and 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 modeling entities and relationships as a property graph.
• 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.

Compensation and Location

• Location: San Diego, CA (onsite)
• Salary Range: USD 87,100 - 157,450 per year

Benefits

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