Data Engineering Lead: Enterprise Pipelines & AI

Bollinger Shipyards, Inc.

Metairie (LA)

On-site

USD 130,000 - 180,000

Full time

14 days+
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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

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

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