Senior Data Engineer, Manager

This is Us: JS Perkins Consulting (JSPC) delivers value added management and technology consulting services. JSPC is committed to creating trusted partnerships to provide sustainable solutions to meet our client needs. We thrive on respect for the individual and host an open idea meritocracy. Here is the Role : J.S. Perkins Consulting is seeking a Senior Data Engineer to support a mission-critical Defense Health data modernization initiative. The program is building an enterprise data orchestration layer across a large, federated defense health data landscape. The work connects clinical, operational, financial, and readiness source systems to a modern enterprise data platform, then curates that raw data into governed, well-documented silver and gold data products that mission users can trust and reuse. The model is federated: data stays with its authoritative owners, and the orchestration layer makes it discoverable, interoperable, and consumable through catalogs, APIs, and a data product marketplace. In this role you will serve as a senior technical contributor, delivering production-ready data capabilities while establishing reusable patterns for ingestion, integration, and delivery. You will take on the harder integration problems, help shape how ingestion and curation are done consistently across pipeline and product teams, and support other engineers working through unfamiliar systems. This is a senior individual contributor role with real technical depth, not a management position. What do we offer: Medical/Dental/Vision 401K (up to 5% match) 11 Paid Holidays 4-5 weeks PTO (depending on level) Bonus Incentives Professional Development Telework Continuing Education Credit Your Responsibilities: Design, build, and operate scalable, production-ready data pipelines and data products using Apache Spark with Python and SQL in a Databricks environment Lead the integration and transformation of complex data from diverse defense and federal health systems into reliable, reusable silver and gold data products Design scalable approaches for data ingestion, integration, and exchange across a federated data landscape, including API-based integrations and services Establish and promote reusable data engineering patterns, standards, and best practices that improve consistency, scalability, and maintainability across data products Provide technical guidance on data architecture, pipeline design, data modeling, and integration approaches Define and implement data validation, quality, and governance practices, including data quality rule frameworks and anomaly detection, that make data products trustworthy at every layer Optimize Delta Lake and Databricks performance for large-scale, high-volume workloads Troubleshoot complex technical and data integration challenges, identify root causes, and drive durable solutions rather than repeat fixes Partner with subject matter experts and functional owners to decode complex business logic and convert domain knowledge into defensible technical data requirements Ensure data products carry the metadata, lineage, and documentation required for enterprise catalog registration and customer data governance expectations Provide technical guidance and mentorship to other engineers, helping the team navigate complex or unfamiliar technical challenges Proactively identify opportunities to improve engineering tooling, process, and patterns, and help drive their adoption Collaborate with engineers, architects, analysts, and customer stakeholders to translate complex data needs into scalable technical solutions What you bring: 8 or more years of data engineering, software engineering, or closely related technical experience Extensive hands-on experience designing, building, and operating production data pipelines and data products at scale Expert-level SQL. Able to write, optimize, and debug complex queries for large-scale analysis and transformation, including complex joins, window functions, and common table expressions Advanced proficiency with Python Strong experience with Apache Spark and distributed data processing across clusters Deep familiarity with the Databricks platform, including workspace management, notebook collaboration, and Delta Lake optimization Experience designing and maintaining ETL and ELT processes for complex, large-scale datasets Experience integrating data across disparate systems and consuming or developing API-based data integrations Strong understanding of data modeling, data architecture, data quality, and data governance principles, including establishing data quality rules and anomaly detection Experience troubleshooting and optimizing complex production pipelines for performance, reliability, and scalability Experience with Git-based development workflows, code review, and modern software engineering practices Comfort working in terminal and command-line environments Demonstrated experience providing technical guidance, mentoring engineers, and influencing engineering practice Ability to proactively engage subject matter experts, decode complex business logic, and set technical data requirements from it Strong client and stakeholder communication skills, with the ability to translate technical concepts and recommendations for both technical and non-technical audiences Ability to independently navigate ambiguity, identify technical risk, and drive complex engineering challenges to resolution across multiple concurrent workstreams Experience spotting security, privacy, and compliance issues and working them with the appropriate stakeholders Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field U.S. citizenship, and the ability to obtain and maintain a DoW Secret clearance Travel Requirements: Must be willing to travel for client business as needed. Physical Requirements: Work is performed in hybrid/remote office environment and requires operating standard office equipment and keyboards. Must be able to lift small packages or other items up to 20 lbs and travel short or long distances in a car, airplane, or other vehicle of transportation to client destinations nationally and internationally if needed. Preferred Experience: Active DoW Secret clearance or higher at time of application Master's degree in Computer Science, Engineering, Data Science, or a related technical field GitLab experience, including code versioning, peer review, and managing CI/CD deployment pipelines AWS or other cloud platform experience Experience with Advana, the War Data Platform, Palantir Foundry, or similar DoW data environments Experience with very large datasets, including datasets containing billions of records Experience with defense health, federal health, financial, or other regulated and sensitive data, including PHI and PII handling under HIPAA Familiarity with health data standards such as HL7 or FHIR, ICD-10, or CPT Experience standing up or operating a data mesh, data product, or federated data governance model Experience with data catalog, metadata, and lineage tooling and enterprise data product registration Experience using AI-assisted development tools to accelerate engineering, testing, documentation, and debugging Culture Statement: At JS Perkins Consulting, we believe our people are the foundation of our success. Because of this, we value talent and drive, celebrate individuality, embrace diversity, and inspire authenticity. We have a culture of mutual trust and respect and believe everyone has a voice. JSPC goes above and beyond for the client and each other. EEO Statement: JSPC is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws . This policy applies to all employment practices within our organization . JS Perkins Consulting makes hiring decisions based solely on qualifications, merit, and business needs at the time.