Sr. Engineering Manager - Data Platform

Role overview A senior engineering leader is needed to head the data platform organization that underpins a large-scale, AI-enabled business operating system used by agencies and SMBs worldwide. This is a hands-on people-leadership role focused on setting data infrastructure strategy, partnering with Product, Engineering, Finance, and Go-to-Market leaders, and raising trust in data across the company.

Responsibilities - Recruit, mentor, and grow a high-performing data platform engineering team, including senior technical leaders and succession depth. - Define and drive the multi-quarter data infrastructure roadmap, including architecture, data flow design, platform abstractions, APIs, and SLAs. - Partner with Product, Data, and Finance leadership to plan and sequence initiatives that power analytics, reporting, experimentation, and machine learning. - Ensure resilience, observability, incident response, disaster recovery, and cost efficiency across the platform. - Establish organization-wide standards for pipeline reliability, data quality, governance, and security in collaboration with Security, Audit, and Analytics Engineering. - Manage headcount and vendor budgets, and champion engineering best practices that balance execution speed with long-term scalability.

Requirements - 10+ years in software engineering, SRE/infrastructure, data platform engineering, or a related field. - 4+ years managing and developing high-performing technical teams. - Deep hands-on expertise with modern data warehouses such as Snowflake, BigQuery, or Databricks, and orchestration/transformation tools like Airflow and DBT. - Experience defining data security posture, platform SLAs, and governance frameworks. - Strong grasp of data warehousing concepts, infrastructure workload management, Git, and CI/CD workflows. - Proven ability to influence technical strategy across multiple organizations and communicate with executive stakeholders.

Nice to have - Experience scaling platform teams through rapid company growth. - Familiarity with event-driven architectures, data science and product analytics workloads, experimentation platforms, ML initiatives, and executive KPI frameworks. - Track record of delivering customer-facing data products.

Benefits and work setup - Remote-first organization with global teammates. - U.S. annual compensation range of approximately $220,000–$291,000, depending on location and experience. - Equal opportunity employer with affirmative action compliance.