Sr. Engineering Manager - Data Platform

gohighlevel; United States; Remote; USD 220,000 - 291,000; Full time

Benefits offered by this job

Remote-first organization

Competitive compensation

Job summary

gohighlevel seeks a senior data platform engineering leader who will head the data infrastructure organization powering a large AI-enabled business operating system used by agencies and SMBs worldwide.

You will recruit, mentor, and shape a high-performing team while defining a multi-quarter data roadmap, balancing speed with long-term scalability, and partnering with Product, Finance, and GTM leaders to enable analytics, ML, and experimentation at scale.

Qualifications

• 10+ years in software engineering, SRE/infrastructure, data platform engineering, or a related field.
• 4+ years managing and developing high-performing technical teams.
• Hands-on expertise with Snowflake, BigQuery, Databricks, Airflow, and DBT.
• Experience defining data security posture, platform SLAs, and governance.
• Strong knowledge 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.

Responsibilities

• Recruit, mentor, and grow a high-performing data platform engineering team.
• Define and drive multi-quarter data infrastructure roadmap (architecture, data flow, APIs, SLAs).
• Partner with Product, Data, and Finance to plan analytics, reporting, experiments, and ML initiatives.
• Ensure resilience, observability, incident response, disaster recovery, and cost efficiency.
• Establish standards for data quality, governance, and security with Security and Analytics teams.
• Manage headcount and budgets, and promote scalable engineering practices.

Skills

Team leadership

Executive communication

Strategic influence

Data platform vision

Reliability & security

Cross-functional collaboration

Tools

Snowflake

BigQuery

Databricks

Airflow

DBT

Git

CI/CD

Job description

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.