Engineering Manager, Data Platform and Governance

Canopy•Detroit, MI

1d•Hybrid

About The Position

We are seeking an Engineering Manager, Data Platform & Governance to lead the development of our data capabilities and governance practices across connected security products and cloud services. This role will be responsible for defining and executing our data strategy, building scalable data platforms and analytics capabilities, and establishing the governance, privacy, and compliance foundations required to support a growing connected-product ecosystem. The ideal candidate combines strong engineering leadership with deep expertise in data architecture, analytics, governance, and cloud technologies. As part of a fast-moving organization focused on AI-powered vehicle security solutions, this leader will partner closely with Product, Software Engineering, AI/ML, Security, Legal, and our parent company's digital teams to ensure that data is accurate, trusted, secure, and actionable. They will help transform data generated from connected devices, cloud services, customer interactions, and AI systems into insights that drive product innovation, operational excellence, and business growth. This is a highly cross-functional role with significant influence on our data strategy, technology roadmap, compliance posture, and future initiatives.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field.
8+ years of experience in software engineering, data engineering, analytics engineering, data science, or related disciplines.
3+ years of experience leading technical teams, including hiring, mentoring, performance management, and technical leadership.
Experience designing and operating modern cloud-based data platforms and data pipelines.
Strong understanding of data warehousing, data lakes, ETL/ELT architectures, data modeling, and data integration patterns.
Proficiency with SQL and at least one modern programming language such as Python, Java, or Scala.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience implementing data governance frameworks, data quality programs, and data lifecycle management practices.
Working knowledge of privacy and data protection regulations, including GDPR and CCPA.
Experience building analytics solutions, dashboards, and KPI frameworks that support business decision-making.
Strong stakeholder management, communication, and collaboration skills.
Proven ability to balance strategic planning with hands-on technical execution.

Nice To Haves

Master's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field.
Reside within the Detroit, Michigan area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.

Responsibilities

Define and execute the company's data platform, analytics, and governance strategy.
Build and lead a high-performing team of data engineers, analytics engineers, data scientists, and analysts as the organization grows.
Establish technical roadmaps, architecture standards, and best practices for data systems and services.
Partner with executive leadership to identify opportunities to leverage data for product innovation, customer experience, operational efficiency, and business growth.
Develop metrics and KPIs that measure product performance, customer engagement, and business outcomes.
Lead the development of data pipelines, ETL/ELT processes, streaming architectures, and data integration solutions.
Establish data quality, observability, lineage, cataloging, and reliability practices.
Develop dashboards and data products that provide actionable insights to engineering, product, operations, and leadership teams.
Develop and maintain enterprise data governance policies, standards, and operating procedures.
Define data ownership, stewardship, retention, classification, and lifecycle management processes.
Lead initiatives related to privacy, consent management, and regulatory compliance, including GDPR, CCPA, and other applicable regulations.
Partner with Security, Legal, and Compliance teams to implement controls that protect customer and product data.
Establish auditability, data access controls, and governance processes for AI and analytics workloads.
Support security reviews, risk assessments, compliance audits, and customer data inquiries.