Senior Data Engineer

Systems Planning and Analysis•Alexandria, VA

About The Position

Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted. As a Senior Data Engineer, you will design, build, and operate enterprise data pipelines and data models that transform operational data into secure, trusted, and accessible data products. This position works closely with Finance, Accounting, HR, Business Development, and SPA’s client‑facing business units - requiring strong communication skills to translate technical concepts into clear, actionable information for diverse stakeholders.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Science, or related field.
7+ years of experience building production‑grade data pipelines and data models on modern cloud platforms.
Experience supporting BI environments and semantic modeling (e.g., Power BI).
Experience with data warehousing, Lakehouse architectures, ETL/ELT patterns, and data quality frameworks.
Demonstrated ability to explain technical concepts clearly and concisely to non‑technical audiences.
Experience with MDM tools, middleware integrations, or enterprise master data synchronization.
Experience with Azure data services, orchestration tools, and enterprise analytics platforms.
Excellent communication skills - written, verbal, and visual - with the ability to tailor messaging to executives, business users, and engineering peers.
Proven record of effective collaboration with cross‑functional stakeholders.

Nice To Haves

Background in government‑contracting or regulated environments.
Good SQL skills and proficiency in a programming language such as Python or Scala.
Exposure to process engineering and change‑management practices.

Responsibilities

Data Engineering & Architecture
Design, develop, and maintain scalable data pipelines and workflows across enterprise systems.
Build well‑structured data models, semantic layers, and curated datasets aligned with business needs.
Implement data quality, observability, and reliability controls to ensure accuracy and auditability.
Integration, MDM & Platform Operations
Engineer integrations that synchronize master data across SPA systems.
Partner with enterprise platform teams to leverage SPA‑approved middleware, MDM, and Azure services.
Implement CI/CD, IaC, and automation to manage data environments and deployments.
Communication & Cross‑Functional Collaboration
Translate complex data engineering topics into clear, plain‑language explanations for business, technical, and executive audiences.
Work directly with stakeholders to understand data needs, document requirements, and communicate technical impacts.
Act as a trusted partner to business units, collaborating on reporting, analytics, and process‑improvement initiatives.
Provide clear written documentation, diagrams, and briefings that support data governance, solution design, and adoption.
Security, Governance & Compliance
Implement secure data access patterns, encryption, retention, and lineage in alignment with SPA cybersecurity and compliance requirements.
Support enterprise data governance practices and contribute to standardized data policies and definitions.
BI & Analytics Enablement
Partner with analysts to deliver high‑quality, consumption‑ready datasets for reporting tools.
Provide guidance on data modeling, semantic layers, and best practices for BI enablement.
Continuous Improvement
Contribute to engineering standards, patterns, and documentation.
Mentor junior engineers and analysts in engineering practices and communication techniques.