Director, Data Engineering

Dwyer Instruments, PTY; Michigan City (IN); On-site; USD 180,000 - 240,000; Full time

Job summary

Dwyer Instruments, PTY seeks a Director of Data Engineering to architect a data lakehouse-driven platform enabling real-time analytics and AI-ready workflows across manufacturing and sales data. You will lead a cross-functional team to integrate OT, ERP, and commerce data into a unified data ecosystem.

Ideal candidates bring 15+ years in data strategy with 5+ years in leadership, and a proven track record deploying lakehouse architectures and enterprise AI/ML initiatives.

Qualifications

• 15+ years in data strategy, architecture, and engineering.
• 5+ years in a leadership role driving data & analytics teams.
• Lakehouse architecture design and deployment at scale (Databricks/Snowflake).
• Proven experience operationalizing AI/ML models in enterprise environments.
• Cloud data stacks experience (Azure Synapse/Fabric, ADLS Gen2).
• Proficient in Python, Spark, SQL; CI/CD for data pipelines; IaC.
• Bachelor’s or Master’s degree in CS, Data Engineering, or related field.

Responsibilities

• Architecting the Future: Lakehouse-centered data infrastructure roadmap.
• AI-Ready Foundation: Data governance, cataloging, and lineage for trusted AI models.
• Manufacturing Integration: Ingest IIoT and supply chain data with OT/Engineering teams.
• Modern Data Stack Leadership: Transition from legacy BI to self-service analytics.
• Data Ops & Governance: Lead MLOps and DataOps for quality and security.
• Strategic Partnership: Work with business leaders to identify data products with business impact.
• Team Leadership: Build and mentor a team of data engineers, ML engineers, and data architects.

Skills

Strategic thinking

Leadership

Architectural design

AI/ML fluency

Cloud data stacks

Python

Spark

SQL

CI/CD

IaC

Education

Bachelor’s or Master’s in CS/Data Engineering

Tools

Databricks

Snowflake

Azure Synapse

Azure Fabric

ADLS Gen2

Job description

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.