Engineering Manager, Data Platform

Responsibilities

• 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.

Requirements

• 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.
• To effectively support our international teams, this position requires flexibility to overlap with US working hours as needed.
• Be Human With Us:
• Use of AI Technology:

Benefits

Additional Information

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.

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Company Intel

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