Senior Principal Data Analytics Engineer

BAE Systems•Nashua, NH

1d•Onsite

About The Position

As a Senior Principal Data Analytics Engineer at BAE Systems, you will occupy a Mission Critical role at the intersection of software engineering, data analytics, and business intelligence. You will be responsible for supporting and implementing the technical vision for how we transform raw data into actionable insights, moving beyond simple pipelines to build sophisticated, production-grade analytics layers. You will lead the transition toward a modern, self-hosted analytics infrastructure, ensuring that our data is not only accessible but also high-quality, governed, and ready for high-stakes decision-making. You will ensure that our data architecture adheres to stringent security protocols and regulatory requirements with a secure-by-design approach to data democratization.

Requirements

Bachelor’s degree in a technical discipline (Computer Science, Engineering, Mathematics) or equivalent experience.
6+ years of professional experience in data or analytics engineering, with a proven track record of delivering end-to-end analytics solutions.
Expert SQL: Proficent in window functions, CTEs, and complex joins.
Modern Data Stack: Proficient with dbt or similar transformation tool, including macros, packages, and custom testing.
Experience implementing GitOps workflows (GitLab CI/Jenkins) or similar for data pipeline deployment.
Experience with orchestration tools such as Airflow, Prefect, or Dagster, etc.
Proven experience in implementing Data Quality (DQ) frameworks and automated testing (e.g., dbt-tests, Great Expectations, or similar).
Environment: Experience managing data within Postgres, Snowflake, MySQL or similar relational databases

Nice To Haves

Experience with Medallion Architecture design patterns or similar
Knowledge of containerization (Docker/Kubernetes) for hosting data tools.
Familiarity with the defense industry or government contracting data security requirements.
Strong communication skills with the ability to explain complex technical architectures to non-technical stakeholders.
Experience with Infrastructure as Code (Terraform or Pulumi) to manage self-hosted data infrastructure.
Programming: Strong proficiency in Python for data manipulation and microservice integration.

Responsibilities

Advanced Data Modeling: Design and maintain complex data models within a Medallion Architecture, specializing in the Silver and Gold layers to provide optimized datasets for end-user consumption.
Analytics Transformation: Drive the implementation of dbt (data build tool) core on self-hosted environments (e.g., Postgres), emphasizing modularity, version control, and CI/CD best practices.
Data Governance and Lineage: Establish and enforce strict data lineage and cataloging standards to ensure auditability and traceability of mission-critical KPIs.
Strategy & Architecture: Collaborate with leadership to develop a comprehensive data strategy that balances technical debt with the rapid delivery of analytic value. Architect and deploy data tooling within secure, air-gapped, or hybrid-cloud environments, ensuring seamless updates and stability without constant external connectivity.
Performance Optimization: Tune complex SQL queries and optimize data structures to handle large-scale datasets while maintaining cost-efficiency and performance. Optimize the ingestion and transformation of high-velocity telemetry or sensor data, bridging the gap between raw engineering data and executive business intelligence.
Cross-Functional Leadership: Partner with Data Scientists and Business Analysts to understand their requirements and provide the "clean room" data environments they need to succeed.
Mentorship & Standards: Serve as the technical authority for the analytics engineering team, establishing standards for Python-based automation and SQL documentation.