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Director Nhl Data Science Jobs in Indiana (NOW HIRING)

DwyerOmega

Director, Data Engineering

Michigan City, IN · On-site

$165K/yr

We are seeking a visionary Director, Data Engineering to architect the "data set of the future ... Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related ...

New

Munich RE

Principal Data Scientist - FCAS

Carmel, IN · On-site

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Deckers

Director, Data Architecture Reports to: Chief Digital & Data Officer Location: United States ... Bachelor's degree required, preferably in Computer Science, Information Systems, or a related ...

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Infographic showing various Director Nhl Data Science job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Director, Data Engineering

Dwyer Instruments, Inc.

Michigan City, IN • On-site

$165K/yr

Full-time

Posted 5 days ago

Job description

Job Type
Full-time
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.

Salary Description
165,000

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