Director, Data Engineering

This is a fully remote position, open to applicants in Michigan.

📋 Description

• Develop and implement a strategic data infrastructure roadmap focused on Lakehouse architecture.

• Combine structured and unstructured data for real-time analytics and extensive AI/ML applications.

• Create frameworks for data governance, cataloging, and lineage to ensure secure and reliable AI models and LLMs.

• Collaborate with OT and Engineering teams to gather and operationalize IIoT and supply chain data.

• Build a cohesive data ecosystem that enhances predictive maintenance and factory-floor productivity.

• Spearhead the transition from traditional BI tools to contemporary, self-service analytics platforms.

• Champion the adoption of MLOps and DataOps practices.

• Maintain data quality, security, and compliance in automated environments.

• Work with business unit leaders to prioritize data products that drive revenue increases or reduce costs.

• Recruit and mentor a team of data engineers, ML engineers, and data architects.

• Connect cloud-native environments with intricate legacy manufacturing systems.

⛳️ Requirements

• Over 15 years of experience in data strategy, architecture, and engineering.

• Minimum of 5 years in a leadership position fostering organizational change.

• More than 5 years of experience managing data and analytics teams.

• Proven track record in designing and deploying scalable Lakehouse architectures, such as Databricks, Snowflake, or similar platforms.

• Established experience in operationalizing AI/ML models within an enterprise setting.

• Profound understanding of data preparation for LLMs and generative AI technologies.

• Extensive familiarity with Azure or equivalent cloud hyperscaler data stacks, including Synapse/Fabric, ADLS Gen2, and Azure AI.

• Advanced skills in Python, Spark, and SQL.

• Strong experience with CI/CD processes for data pipelines and infrastructure-as-code.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical discipline.

• Experience with data governance frameworks and tools.

• Exposure to advanced analytics, data science, or machine learning projects is advantageous.

• Experience in manufacturing, industrial, or eCommerce sectors is preferred.

• Capability to work in both office and manufacturing settings.

• Willingness to work outside regular business hours, including nights, weekends, and holidays when necessary.

• Ability to sit or stand for extended periods.

• Capacity to lift 30–50 lbs without assistance.

• Valid driver’s license and passport.

• Willingness to travel locally and internationally as required.

🏝️ Benefits

• Flexible fully remote work arrangement.

• Local and/or international travel as necessary (10–15%), including potential extended stays for training or deployments.