Data Engineering Manager

Bollinger Shipyards

$100K — $140K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or related field
  • 8-12 years of experience in data engineering
  • Proven experience delivering enterprise-scale data pipelines
  • Strong SQL and data transformation expertise
  • Experience with cloud data platforms (Azure preferred)
  • Experience integrating ERP and operational systems

Responsibilities

  • Lead the development and support of enterprise data pipelines across various systems
  • Establish and maintain scalable data engineering standards and practices
  • Ensure implementation of enterprise data architecture and design patterns
  • Oversee data ingestion, transformation, and validation processes
  • Partner with teams to align technical solutions with enterprise standards
  • Support analytics and AI initiatives with trusted datasets
  • Manage delivery timelines and technical execution for the team
  • Collaborate with cybersecurity teams for secure data handling
  • Evaluate emerging technologies to enhance data engineering capabilities
  • Mentor and develop technical talent within the team

Benefits

  • Professional development opportunities
  • Access to emerging technologies
  • Collaborative work environment
  • Flexible working arrangements
  • Comprehensive healthcare options
Full Job Description
Job Title: Data Engineering Manager

Location: Multiple Location

Position Overview: The Data Engineering Manager leads 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.

The role partners closely with Enterprise Architecture, Analytics, Data Science, Infrastructure, and business stakeholders to integrate data from ERP, operational, engineering, and manufacturing systems into the enterprise Azure data platform.

Key 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

Qualifications:
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or related field
• 8-12 years of experience in data engineering
• Proven experience delivering enterprise-scale data pipelines
• Strong SQL and data transformation expertise
• Experience with cloud data platforms (Azure preferred)
• Experience integrating ERP and operational systems

Skills and Abilities:
• 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 certifications

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