Data Engineering Manager

Bollinger Shipyards, Inc.; Metairie (LA); On-site; USD 130,000 - 180,000; Full time

Job summary

Bollinger Shipyards, Inc. seeks a Data Engineering Manager to lead design, development, and delivery of enterprise data pipelines and foundational assets supporting analytics, reporting, forecasting, and AI initiatives.

The role emphasizes scalable, reliable data practices and secure, accessible data aligned to business priorities. You will mentor a data team, manage priorities and sprints, collaborate with Architecture, Cybersecurity, and Operations, and drive data quality, lineage, and

Qualifications

• 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 leading data engineering teams and projects.

Responsibilities

• Lead the design, development, and delivery of enterprise data pipelines and data assets.
• Establish scalable data engineering standards and development practices.
• Ensure data quality, lineage, observability, and security across enterprise data.
• Collaborate with Enterprise Architecture, Cybersecurity, and IT teams.
• Mentor and develop technical talent while managing priorities and timelines.

Skills

Azure Synapse

Azure Data Factory

Databricks

Power BI

AI data pipelines

Data observability

Metadata management

Cloud certificates

Education

Bachelor’s degree in Computer Science or related field

Tools

Oracle ERP

Finesse

MES

PLM

Primavera

Job description

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.

POSITION OVERVIEW

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.

REQUIREMENTS

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

SKILLS

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

RESPONSIBILITIES

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