Data Engineering Manager

For nearly a century, Bollinger Shipyards has created a legacy as a leading designer and builder of high-performance marine vessels. We are renowned for delivering top-quality construction, manufacturing, and repair services with a commitment to safety and environmental responsibility.

We are seeking a dedicated Data Engineering Manager with at least a Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Management, or related field. The candidate will lead the design, development, and delivery of enterprise data pipelines and foundational data assets supporting analytics, reporting, forecasting, and AI initiatives. This role is responsible for establishing scalable and reliable data engineering practices while ensuring enterprise data is accurate, secure, accessible, and aligned to business priorities.

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Management, or related field Minimum of 8–12 years of experience in data engineering

Experience with Azure Synapse, Azure Data Factory, Databricks, Fabric, or similar cloud technologies Experience in manufacturing, shipbuilding, industrial, or engineering-intensive environments Familiarity with Power BI and downstream analytics enablement Experience supporting AI/ML initiatives through engineered datasets and feature pipelines Knowledge of data observability, master data management, and metadata management practices Relevant cloud or data engineering certification

Lead the development and support of enterprise data pipelines and integrations across Oracle ERP, Finesse, MES, PLM, Primavera, proposal systems, and other operational platforms Establish and maintain scalable data engineering standards, frameworks, and development practices Ensure consistent implementation of enterprise data architecture and medallion data design patterns (raw, curated, business-ready) Oversee data ingestion, transformation, orchestration, reconciliation, and validation processes Partner with Enterprise Architecture and Integration teams to align technical solutions with enterprise standards and future-state architecture Support analytics, reporting, forecasting, and AI initiatives through delivery of trusted and performant datasets Ensure data quality, lineage, observability, and reliability across enterprise data assets Manage priorities, sprint planning, delivery timelines, and technical execution for the data engineering team Collaborate with cybersecurity and infrastructure teams to ensure secure and compliant handling of enterprise data Evaluate emerging technologies and recommend improvements to data engineering capabilities and platform performance Mentor and develop technical talent while fostering strong engineering discipline and accountability