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Engineering Manager, Data Platform

mntn

Other Full-time Permanent United States

Job details

Not specified Salary
United States Eligibility
Lead Experience
Full-time Employment

About this role

Role overview Lead the internal Data Platform team responsible for the foundational data infrastructure and tooling that empowers data engineers, analysts, and data scientists across the organization. This hands-on engineering leadership role partners with a senior technical leader to define the roadmap, coordinate execution, and ensure delivery of high-leverage tools for internal customers. The scope spans the full lifecycle of an internal data platform treated as a product: ingestion, transformation, orchestration, observability, and governance.

Responsibilities - Direct the design, build, and maintenance of core data infrastructure and tooling that supports analytics, data science, and data engineering workloads. - Co-author the team's technical roadmap and architecture with the senior engineering partner, balancing near-term delivery with long-term platform health. - Collaborate cross-functionally with data science, analytics, product, and engineering teams to understand use cases and shape platform features accordingly. - Ensure high reliability, scalability, and usability across data ingestion, transformation, orchestration, observability, and governance. - Establish and enforce best practices for data engineering and platform development, including standards for code quality, testing, and documentation. - Provide hands-on technical leadership through design discussions, code reviews, and direct contributions on key projects. - Hire, coach, and develop engineers, fostering a culture of technical excellence, ownership, and continuous improvement. - Communicate the platform roadmap, priorities, and ongoing work to stakeholders across the business.

Requirements - 7+ years of software engineering experience, including 2+ years leading teams or projects. - Demonstrated experience building internal platforms or developer tools, ideally in a data-intensive environment. - Strong understanding of modern data infrastructure: orchestration (e.g., Airflow, Dagster), warehousing (e.g., BigQuery, Snowflake), streaming (e.g., Kafka), and transformation tools (e.g., SQLMesh). - Proficiency with cloud infrastructure on AWS or GCP, containers, and infrastructure-as-code. - Ability to lead cross-functional workstreams and translate user needs into robust platform capabilities. - A product mindset focused on solving real user problems, not just building technology for its own sake. - Willingness to remain hands-on and contribute code while growing a high-performing team.

Nice to have - Experience operating an internal data platform as a product with internal SLAs and adoption metrics. - Familiarity with data governance, lineage, and access control patterns in regulated or multi-tenant environments.

Benefits and work setup - Remote-friendly work setup based on the listing. - Emphasis on a people-first culture with a focus on engineering excellence, ownership, and innovation that augments rather than replaces human work.

Skills detected in the listing

GoSnowflakeApache AirflowData EngineeringStakeholder ManagementAWSGCP
Detected Sep 3, 2026
Last verified Sep 3, 2026
Original source: job-boards.greenhouse.io · application link requires Hidden Jobs Access

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