Team Leader

MacLean Engineering is looking to add a skilled and experiencedTeam Lead Dataand Industrial Streamingto join our growing team in Cambridge, Ontario. If you are looking to be challenged, valued, and rewarded with a competitive compensation package in a dynamic work environment, this position is for you At MacLean Engineering, we’re not just building machines — we’re redefining the future of mining through innovation. Inspired by over 50 years of pioneering excellence, MacLean Engineering continues to lead the way in underground mining equipment solutions. Rooted in our founder’s unwavering commitment to safety, productivity, and enduring quality, we are driven by innovation and expansion. With facilities strategically located across Ontario in Collingwood, Owen Sound, Barrie, and Sudbury, and across the globe in Mexico, South Africa, and Australia, our dedicated workforce collaborates in a safety centric environment to deliver superior components and equipment to the underground mining, municipal, environmental, and industrial sectors. The Position: We’re seeking a Team Lead
- Data to stand up and grow a new Data team that will turn telematics and operational data from MacLean’s vehicles into trusted datasets, predictive insights, and customer-facing analytics. If you’re an experienced data engineering leader who wants to build a capability from the ground up – setting the architecture, hiring and mentoring the team, and shipping real products – this role is for you. As the leader of the Data team within the Telematics, Automation, and Controls Division, you’ll define the data strategy, architecture, and delivery roadmap spanning ingestion from vehicles and legacy systems, streaming and storage, governed semantic layers, BI and operational reporting, and machine learning products such as predictive maintenance, root cause diagnostics, anomaly detection, and fleet optimization. You’ll own the end-to-end data platform
- pipelines, datasets, semantic layer, and data APIs
- that moves data from the edge to curated, governed datasets and on to analytics and ML consumers, while partnering cross-functionally with vehicle interface, platform, autonomy, controls, and business stakeholders. You’ll lead a multidisciplinary team spanning analytics, data engineering, and data science – building a culture of engineering rigor, data quality, and business impact. The successful candidate will operate at the intersection of industrial IoT and modern data platforms, designing resilient ingestion pipelines, robust schema and contract management, and production ML workflows that scale across MacLean’s 32+ vehicle types and global footprint. Responsibilities and Duties:
- Lead and grow a multidisciplinary Data team spanning analytics, data engineering, and data science, providing hands-on mentorship in modern data platform practices and setting direction for the function.
- Define and own the end-to-end data architecture (pipelines, datasets, semantic layer, and data APIs
- running on infrastructure provided by the Platform team): vehicle data acquisition (OPC UA), external integrations (MQTT, Sparkplug B, PI, and similar), streaming, raw curated semantic storage layers, and external APIs for data consumers.
- Oversee ingestion from vehicles and CDC from legacy systems, ensuring reliable, low-latency movement of data from the edge into curated, governed datasets.
- Establish and enforce schema management, data contracts, data quality checks, and SLAs across pipelines and datasets.
- Partner cross-functionally with vehicle interface, platform, autonomy, controls, and business stakeholders to translate operational needs into trusted datasets, KPIs, dashboards, and analytics products.
- Drive the BI and reporting practice: KPI definition with business stakeholders, certified datasets and metric governance, operational and executive dashboards, and self-service enablement for business users.
- Drive the data science practice: predictive maintenance, root cause diagnostics, telemetry anomaly detection, fleet optimization, and customer-facing analytics features, with rigorous experimentation and model evaluation.
- Collaborate with the Platform team on MLOps, deploying and monitoring models in production and ensuring reproducibility across training and serving.
- Own data governance, security, and compliance on the data platform, including access control, lineage, auditability, and cybersecurity practices for data at rest and in motion.
- Partner with on-vehicle software and edge-platform teams to define and enforce strict edge-to-cloud data contracts and schema registries.
- Set engineering standards for the team
- code quality, testing, CI/CD, containerized deployment (Docker/Kubernetes), and release governance for pipelines, datasets, and models.
- Help to manage delivery: roadmap, prioritization, hiring, performance, and stakeholder communication, ensuring the team ships measurable business impact. Qualificatio