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Director, Data Engineering

  • Michigan City, IN, United States

$165,000 USD / year

This opening has closed.

The original listing is kept below for reference.

Job details

Pay
$165,000 USD / year
Experience
Strategic Experience: 15+ years in data strategy, architecture, and engineering, with at least 5 years in a leadership role driving organizational change.
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

Description We are seeking a visionary Director, Data Engineering to architect the "data set of the future." This role is not just about reporting; it is about building the scalable, AI-ready infrastructure that will fuel our next generation of manufacturing innovation. You will move the organization beyond traditional data warehousing to a robust Data Lakehouse architecture, ensuring our enterprise data - from shop floor to point-of-sale - is clean, real-time, and ready for advanced GenAI and predictive modeling. The ideal candidate is a technologist who fluently bridges the gap between the plant floor and the front office. You will be responsible for integrating complex operational data with high-velocity sales and commercial data to create a unified ecosystem. By connecting factory efficiency directly to customer demand and market trends, you will enable us to pivot from reactive operations to a truly predictive enterprise.

Key Responsibilities:

  • Architecting the Future: Define and execute a data infrastructure roadmap centered on a Lakehouse architecture that integrates structured and unstructured data, enabling both real-time operational analytics and high-scale AI/ML workloads.
  • AI-Ready Foundation: Establish the data governance, cataloging, and lineage frameworks necessary to power secure, trusted AI models and Large Language Models (LLMs) across the enterprise.
  • Manufacturing Integration: Partner with OT and Engineering teams to ingest and operationalize IIoT and supply chain data, creating a unified data ecosystem that drives predictive maintenance and factory floor efficiency.
  • Modern Data Stack Leadership: Oversee the transition from legacy BI tools to modern, self-service analytics platforms, ensuring the organization has the agility to derive insights from the data lakehouse.
  • Data Ops & Governance: Lead the transition to MLOps and DataOps methodologies, ensuring data quality, security, and compliance in an increasingly automated environment.
  • Strategic Partnership: Collaborate with business unit leaders to identify and prioritize data products that drive measurable top-line growth or operational cost reductions.
  • Team Leadership: Build and mentor a high-performing team of data engineers, ML engineers, and data architects who are comfortable in both cloud-native environments and complex legacy manufacturing systems.

Requirements

Qualifications and Technical Requirements:

  • Strategic Experience: 15+ years in data strategy, architecture, and engineering, with at least 5 years in a leadership role driving organizational change.
  • 5+ years in a leadership role managing data & analytics teams.
  • Architecture Expertise: Demonstrated experience designing and deploying Lakehouse architectures (e.g., Databricks, Snowflake, or similar) at scale.
  • AI/ML Fluency: Proven experience operationalizing AI/ML models within an enterprise environment; deep understanding of data preparation for LLMs and generative AI.
  • Cloud Proficiency: Extensive experience with Azure (or equivalent cloud hyperscaler) data stacks (e.g., Synapse/Fabric, ADLS Gen2, Azure AI).
  • Tooling: Advanced proficiency in Python, Spark, and SQL; strong experience with CI/CD for data pipelines and infrastructure-as-code.
  • Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
  • Soft Skills: A "product manager" mindset for data; the ability to translate complex technical architectural debt into business-friendly value proposition

Essential/Preferred Skills:

  • Experience with data governance frameworks and tools.
  • Exposure to advanced analytics, data science, or machine learning initiatives.
  • Experience in manufacturing, industrial, or eCommerce environments preferred.

Work Conditions and Physical Requirements:

  • Ability to work in both office and manufacturing environments.
  • Availability to work outside of core business hours, including nights, weekends, and holidays when required for system upgrades or migrations.
  • Required to sit or stand for long periods of time.
  • The ability to lift 30-50 lbs without assistance.
  • Local and/or international travel will be required as needed (10-15%) including some extended stays on location for education or deployments. Must have a valid driver's license and Passport.
More about this job

Skills

  • Data engineering
  • Data warehousing
  • Point of sale
  • Sales
  • Unstructured data
  • ML
  • Cataloging
  • Supply chain management
  • Leadership
  • Regulatory compliance
  • Team leadership
  • Data analysis
  • Databricks
  • Snowflake
  • Microsoft Azure
  • Python
  • Apache Spark
  • SQL
  • CI/CD
  • Infrastructure as code
  • Computer science
  • Machine learning
  • Valid driver's licence

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