Data Engineering Manager

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