Senior Data Pipeline Engineer (Temp)

RTX•Lexington Park, MD

3d•$52 - $98•Onsite

About The Position

We are seeking a temporary Senior Data Pipeline Engineer to support a growing Data Analytics & Systems Engineering team within the Transformation & Initiatives (T&I) organization. The engineer will contribute senior level technical execution in data engineering, analytics, Extract Transform Load (ETL) pipeline development, AI/ML‑enabled analysis, and systems-level data integration supporting Raytheon programs. This is an experienced technical contributor role. The engineer independently executes complex analytics and integration tasks, supports multi‑disciplinary engineering teams, and advances improvements in data workflows and processes. In addition, the engineer provides day‑to‑day technical guidance and direction to early‑career engineers, ensuring high‑quality execution and consistent engineering practices across the team while contributing significantly to the broader engineering transformation effort. This position is located onsite in Lexington Park, MD.

Requirements

Typically requires a bachelor’s degree in science, technology, engineering or mathematics (STEM) discipline and 8+ years of prior relevant experience
Experience with Python, SQL, and modern data engineering workflows.
Experience performing data analysis, automation, or ETL development.
Systems engineering fundamentals (requirements, integration, documentation).
Ability to obtain and maintain a U.S. security clearance, U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.

Nice To Haves

Experience with Snowflake, ClickHouse, Apache Superset, Power BI, Tableau, or similar analytical tools.
Experience building automation, dashboards, or predictive analytics models.
Familiarity with AI/ML techniques (forecasting, anomaly detection, NLP).
Background in defense systems engineering, sensors, radars, or weapon systems (preferred but not required).
Background in radar, sensors, command & control, or complex defense systems (desired but not required).

Responsibilities

Build, maintain, enhance, and troubleshoot ETL pipelines and engineering data workflows.
Support development and apply analytics using Python, SQL, and enterprise data platforms (Snowflake, ClickHouse, Superset, Power BI, Tableau).
Perform data modeling, statistical analysis, trend identification, and automation to support program decision-making.
Implement ML- or NLP‑based analytic modules (e.g., anomaly detection, ambiguity analysis) under technical direction.
Support system-level data integration, requirements traceability, and cross-tool alignment.
Assist with preparation of technical documentation, process artifacts, and repeatable workflows that improve engineering efficiency.
Ensure data quality, validation, and consistency across engineering baselines.
Collaborate with engineering, program management, and operations teams to translate data into actionable insights.
Communicate results clearly to technical audiences and internal stakeholders.
Provide mentorship to early-career engineers or interns on tools and analytical methods.