Manager Data Platform Engineering

Job Summary

Join a company dedicated to making the world measurably better through advanced ceramics manufacturing. The Data Platform Engineering Manager (Governance & Quality) will lead the strategy, stability, governance, and adoption of the organization’s modern data platform.

Responsibilities

• Execute and deliver against the data platform roadmap aligned to business and analytics strategy.
• Contribute to and implement architectural decisions related to data ingestion, transformation, modeling patterns, Lakehouse architecture, medallion design, and Semantic and consumption layer strategy across Power BI and Sigma.
• Ensure platform scalability, performance, cost optimization, and future-readiness.
• Provide strong input for and introduce new platform capabilities, tooling, and automation to improve platform maturity.
• Manage platform reliability, availability, and performance monitoring.
• Establish and manage SLAs / SLOs for data pipelines and analytics workloads, incident management and root cause processes, platform governance, security, and access patterns.
• Partner with infrastructure / cloud teams and provide input on environment strategy, workspace management, cost visibility and optimization.
• Coordinate with Data & Analytics leadership to ensure data platform production readiness standards for data products and pipelines.
• Support adoption of the data platform and self-service analytics capabilities.
• Define standards for data product design, dashboard and analytics development, documentation and discoverability.
• Lead user enablement initiatives such as training programs, office hours and community of practice, analytics governance forums.
• Partner with business teams to identify high-value use cases and accelerate delivery.
• Lead and develop a team of data engineers, analytics engineers, or platform specialists.
• Establish delivery frameworks and prioritization processes.
• Promote modern engineering practices including CI/CD for data pipelines, Testing and observability, Agile / product-oriented operating models.
• Collaborate closely with Data & Analytics leadership to ensure platform investments drive measurable business outcomes.

Requirements

• Bachelor’s degree in Engineering, Computer Science, Data Science or Information systems or equivalent work experience.
• 7+ years of experience in data engineering, analytics engineering, or data platform leadership.
• 3+ years of experience leading technical teams.
• Hands-on experience with Databricks / Lakehouse architectures.
• Strong familiarity with modern BI and semantic consumption patterns (Power BI, Sigma, or similar).
• Experience managing production data platforms in cloud environments (Azure, AWS, or GCP).
• Proven ability to drive platform adoption and organizational change.
• Strong stakeholder engagement and communication skills.

Preferred Qualifications

• Experience in manufacturing, industrial, or operational analytics environments.
• Knowledge of data governance frameworks and data product operating models.
• Experience with cost optimization and FinOps practices in analytics platforms.
• Familiarity with orchestration tools, data ingestion tooling, and modern ELT patterns.
• Exposure to machine learning platform enablement or MLOps.