Job Description
Req ID: 47069 Team: T56 AI and Digital Innovation Entity: Newport News Shipbuilding US Citizenship Required for this Position: Yes Full-Time Shift: 1st Relocation: No relocation assistance available Virtual/Telework Opportunity: Yes - Occasional or hybrid telework available Travel Requirement: Yes, 10%-25% of the time Clearance Required: No - Clearance Not Required to Start Meet HII’s Newport News Shipbuilding With more than 25,000 employees – including third-, fourth- and even fifth-generation shipbuilders – HII’s Newport News Shipbuilding (NNS) division is the largest industrial employer in Virginia. We’re the sole designer, builder and refueler of U.S. Navy nuclear aircraft carriers and one of two providers of U.S. Navy nuclear submarines. Our diverse and innovative team of professionals ranges from skilled trades to project managers, engineers and software developers to solution architects, technical subject matter experts, and system users. Anchored in our rich, 135-year history, we collaborate together at the forefront of technology, manufacturing, and integration of the most powerful and survivable naval ships in the world. Want to be part of the team? Apply today! We look forward to meeting you. The Role Design, develop, and test operating systems-level software, compilers, and network distribution software. Set operational specifications, and formulate and analyze software requirements. May design embedded systems software. We are looking for a highly skilled Data Engineer to join our Data Science team. In this role, you will collaborate closely with data scientists, analysts, and IT partners to build the data platforms, pipelines, and tooling needed to enable advanced analytics, machine learning, and enterprise-wide data-driven decision making. This is a senior-level engineering position responsible for designing, developing, and maintaining robust, scalable data solutions that power high‑impact models and analytical insights. Key responsibilities include Architect, build, and optimize data pipelines and workflows that support machine learning, statistical modeling, and analytics use cases. Partner with data scientists to operationalize models, including feature engineering pipelines, model ingestion, and production deployment patterns. Design and maintain scalable data environments (data lakes, warehouses, streaming platforms) with a focus on performance, security, and data quality. Develop and enforce best practices for data governance, workflow orchestration, documentation, and code quality. Conduct root-cause analysis on data issues and improve reliability, observability, and monitoring of data systems. Mentor junior engineers and contribute to team-wide technical standards, patterns, and reusable components. Collaborate with cross-functional teams to understand data requirements and translate them into robust engineering solutions. Must Have Bachelor's Degree and 5 years of relevant exempt experience; Master?s Degree and 3 years of relevant professional experience; Ph.D. and 0 years of experience. One of the following may be used as an equivalent to Bachelor's Degree for Information Technology Related Positions Only: NNS Apprentice School graduate Navy Nuclear Power School (NNPS) graduate Associate's Degree or other formal 2 year program and 2 years of relevant exempt experience or 4 years of relevant non-exempt experience Military Paygrade E-5 or above military experience High School/GED and 4 years combined of Manufacturing, Shipbuilding, Trades, Military experience or other relevant exempt experience High School/GED and 8 years combined of Manufacturing, Shipbuilding, Trades, Military experience or other relevant non-exempt experience A relevant professional certification can be substituted for a Bachelor's Degree. Bachelor’s degree in Computer Science, Engineering, or related field. 5 years of experience in data engineering or software engineering with a focus on data-intensive applications. Master's degree and 3 years of relevant experience. PhD and 0 years of experience. Strong proficiency in Python, SQL, and modern data engineering frameworks. Hands-on experience with cloud data platforms (Azure, AWS, GCP). Expertise with distributed data technologies (Spark, Databricks, Hadoop, Kafka, etc.). Experience developing production-grade ETL/ELT pipelines and orchestration tools (Airflow, Azure Data Factory, Dagster). Familiarity with machine learning workflows and supporting data science teams. Nice to Have Experience deploying and monitoring machine learning models in production.