Engineering Manager, Data Platform

Ready to be a Titan? We're looking for an experienced Engineering Manager to join our Data & Reporting Platform team. In this role, you'll own the technical direction and day-to-day execution of a team building the data infrastructure that powers the enterprise. You'll balance hands-on architectural guidance with people leadership — helping engineers grow while ensuring the platform is reliable, scalable, and aligned to business needs. What you'll do: Lead and Mentor: Manage and grow a team of 5 data engineers. Set clear expectations, provide regular feedback, and invest in career development. Build a team culture rooted in ownership, craftsmanship, and psychological safety. Architectural Leadership: Drive architectural decisions across the platform, with particular depth in Data Sharing and Semantic Layer design. Ensure systems are built for high availability, scalability, and security. Technical Excellence: Guide the team through complex technical challenges, including Semantic Modeling, data mesh patterns, and platform reliability. Hold a high bar for code quality, testing, and observability. Performance Optimization: Lead efforts to improve query performance and platform efficiency so that data consumers across the organization can access what they need quickly and reliably. Strategic Execution: Collaborate with product managers and architects to define and deliver the data platform roadmap. Translate business requirements into technical priorities and communicate trade-offs clearly. Operational Health: Own the operational posture of the platform — monitoring, alerting, incident response, and on-call rotation management. Establish and report on team-level operational metrics. Governance & Process: Define engineering best practices and champion shift-left data governance, including data quality, lineage, and access control. What you'll bring: Experience: 8 years in data or software engineering, with 2 years managing engineering teams of 5 or more. Architectural Depth: Proven experience designing complex data systems, with specific expertise in Semantic Layering and Data Sharing at enterprise scale. Modern Tooling: Deep, hands-on experience with dbt and semantic models (eg MetricFlow) — including designing and scaling semantic models in production. Strong proficiency with Snowflake and SQL. Experience with Spark, Python, and Snowpark is a plus. Technical Breadth: Hands-on experience with technologies such as Cursor, Claude CLI/Code, Kibana, and Airflow. Operational Rigor: Experience owning on-call processes, managing incidents, and defining operational metrics that drive team accountability. Engineering Standards: Solid command of CI/CD practices (e.g., GitHub Actions) and data observability tooling such as DataDog or Monte Carlo. Communication: Strong written and verbal communication skills. Able to align cross-functional stakeholders, articulate technical trade-offs, and influence architectural direction without direct authority. Be Human With Us: Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re solving. We’re in this together. Come be human, with us. Use of AI Technology: We use technology, including automated and AI-assisted tools, to support certain aspects of our recruitment process. These tools are designed to improve efficiency and enhance the candidate experience. AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams. What We Offer: When you join our team, you’re not just accepting a job. You’re making a career move. Here’s how we’ll support you in doing some of the most impactful work of your career: Flextime, recognition, and support for autonomous ... (truncated, view full listing at source)