Sr. Engineering Manager - Data Platform at HighLevel

Job description

About HighLevel: HighLevel is an AI-powered business operating system that gives agencies, entrepreneurs and SMBs the infrastructure to build, automate and scale. Today, HighLevel supports SMBs across 150+ countries, fueling community-driven growth rooted in real customer outcomes. To date, businesses operating on HighLevel have generated over $7 billion in ecosystem value, demonstrating the impact of shared infrastructure at scale. By centralizing conversations, automation and intelligence into one system, we help businesses move faster, reduce complexity and execute efficiently. Behind the platform, HighLevel powers more than 4 billion API hits and 2.5 billion message events daily. With 250 terabytes of distributed data, 250+ microservices and over 1 million domain names supported, our architecture is built for performance, resilience and long-term scalability. Our People With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home. Our Impact Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We’re proud to be a part of that. Learn more about us on our YouTube Channel or Blog Posts . About the Role: We are looking for a Senior Engineering Manager to lead our Data Platform & Infrastructure team. This leader will own the strategy, execution, and evolution of the foundational data systems that power insights and our ecosystem. You will lead a team of highly capable engineers responsible for building reliable, scalable, secure, and developer-friendly data infrastructure. This includes data ingestion and processing, data platforms, storage and compute, orchestration, observability, and the infrastructure that enables teams across the company to efficiently build and operate data-intensive products and applications. This is a hands-on leadership role: you will set technical direction and organizational strategy while remaining close enough to the technology to make high-quality architectural decisions and guide the team through complex technical challenges. Responsibilities: Leadership & Team Management Lead, recruit, and mentor an exceptional engineering team. Direct data infrastructure strategy to drive business and product success. Oversee resource allocation, including headcount and vendor budget planning. Establish operational rhythms, goals, and execution frameworks aligned with core business outcomes. Cultivate an inclusive environment focused on ownership, technical rigor, and continuous professional development. Champion team morale, engagement, learning opportunities, and delivery velocity. Data Engineering Strategy Guide system architecture, data flow design, quality standards, and platform roadmaps. Partner with Product and Data leadership to plan, sequence, and execute multi-quarter initiatives. Define robust platform abstractions, APIs, and SLAs to streamline developer workflows and increase adoption. Ensure infrastructure resilience through comprehensive monitoring, incident management, disaster recovery, and cost optimization. Work cross-functionally with Security, Audit, and Analytics Engineering to deploy key capabilities and compliance controls. Cross-Functional Partnership Engage with Data, Product, and Finance partners to enable machine learning, experimentation, and business reporting. Establish and enforce organization-wide standards for pipeline reliability, data security, and quality. Technical Leadership Advocate for automation, engineering best practices, and thoughtful trade-offs between execution speed and long-term scalability. Thrive in fast-paced, ambiguous settings while cultivating senior technical leaders and building leadership succession through delegated autonomy, developing senior technical leaders and succession depth. Requirements: Required Qualifications 10+ years of experience in software engineering, SRE or infrastructure, data platform engineering, or related fields. 4+ years managing high-performing technical teams, growing and developing people Deep expertise with Snowflake/Google BigQuery/Databricks or equivalent modern data warehousing systems and ecosystem of tools including Airflow, DBT etc. Familiarity with Git and CI/CD workflows Strong understanding of data warehousing concepts and infrastructure workload management. Experience defining data security, platform SLAs and governance frameworks. Excellent stakeholder management and communication skills. Demonstrated ability to influence technical strategy across multiple organizations. Preferred Qualifications Experience delivering customer-facing data products is a plus Experience scaling platform organizations through rapid company growth. Familiarity with event-driven data architectures, data science & product analytics computational needs and patterns is a plus. Experience supporting experimentation platforms and machine learning initiatives. Knowledge of metrics governance and executive KPI frameworks. Success in your First Year: Within your first 12 months, you will: Build strong relationships with leaders across Product, Engineering, Finance, and Go-to-Market. Improve trust in data through stronger governance and controls. Increase data consumptions and data-powered products across the organization. Establish scalable development standards and improve engineering velocity. Grow and mentor a high-performing data platform engineering team. Deliver a roadmap that supports both current business needs and future scale. EEO Statement: The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision. We encourage you to review our Privacy Policy before submitting your application

Requirements

Must-haves

Leadership & Team Management
Lead, recruit, and mentor an exceptional engineering team.
Direct data infrastructure strategy to drive business and product success.
Oversee resource allocation, including headcount and vendor budget planning.
Establish operational rhythms, goals, and execution frameworks aligned with core business outcomes.
Cultivate an inclusive environment focused on ownership, technical rigor, and continuous professional development.
Champion team morale, engagement, learning opportunities, and delivery velocity.
Data Engineering Strategy
Guide system architecture, data flow design, quality standards, and platform roadmaps.
Partner with Product and Data leadership to plan, sequence, and execute multi-quarter initiatives.
Define robust platform abstractions, APIs, and SLAs to streamline developer workflows and increase adoption.
Ensure infrastructure resilience through comprehensive monitoring, incident management, disaster recovery, and cost optimization.
Work cross-functionally with Security, Audit, and Analytics Engineering to deploy key capabilities and compliance controls.
Cross-Functional Partnership
Engage with Data, Product, and Finance partners to enable machine learning, experimentation, and business reporting.
Establish and enforce organization-wide standards for pipeline reliability, data security, and quality.
Technical Leadership
Advocate for automation, engineering best practices, and thoughtful trade-offs between execution speed and long-term scalability.
Thrive in fast-paced, ambiguous settings while cultivating senior technical leaders and building leadership succession through delegated autonomy, developing senior technical leaders and succession depth.

Nice-to-haves

Experience delivering customer-facing data products is a plus
Experience scaling platform organizations through rapid company growth.
Familiarity with event-driven data architectures, data science & product analytics computational needs and patterns is a plus.
Experience supporting experimentation platforms and machine learning initiatives.
Knowledge of metrics governance and executive KPI frameworks.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapimachine learningci/cdgo

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Professional Development