# Senior Manager

**Company:** [GoHighLevel](https://hotfix.jobs/companies/gohighlevel)
**Location:** Remote
**Role:** Data Engineering
**Experience:** 11+ years
**Skills:** SQL, dbt, Snowflake, Airflow, Git, CI/CD, dimensional modeling, semantic layers, Data Warehousing, Data Governance, Data Quality, bi platforms
**Posted:** 2026-07-20

> Lead a team of analytics engineers building the semantic metrics layer and scalable data models that power company-wide decision making, reporting, experimentation, and AI products. Requires 11+ years analytics engineering experience including 3+ years managing technical teams, deep SQL and DBT/Snowflake expertise, and strong cross-functional stakeholder skills.

## Job Description

## Responsibilities

**Leadership & Team Management**
- Hire, develop, and lead a high-performing team of Analytics Engineers
- Foster a culture of technical excellence, ownership, continuous learning, and collaboration
- Provide coaching, career development, and regular performance feedback
- Establish team goals, operating rhythms, and execution processes that align with company priorities to deliver business impact

**Analytics Engineering Strategy**
- Define and execute the roadmap for analytics engineering, data modeling, semantic layers, and analytics infrastructure
- Build scalable dimensional models and curated datasets that enable trusted reporting and advanced analytics
- Drive adoption of analytics engineering best practices including testing, documentation, version control, CI/CD, and code review
- Own data quality initiatives, observability, lineage, and governance across the analytics ecosystem
- Continuously improve developer productivity and platform scalability

**Cross-Functional Partnership**
- Partner with peers on the Data team and business stakeholders to understand evolving analytical needs and translate them into scalable data products
- Collaborate with Data Engineering to improve data pipelines, ingestion, orchestration, and warehouse performance
- Work alongside Product Analytics & Data Science to enable experimentation, machine learning, and advanced analytics
- Support Finance and Executive Leadership with trusted metrics and executive reporting
- Help establish company-wide metric definitions and ensure consistency across teams

**Technical Leadership**
- Set standards for data modeling, transformation, documentation, and testing
- Guide architectural decisions for the analytics stack and evaluate new technologies
- Ensure analytics infrastructure scales with rapid business growth
- Review technical designs and mentor engineers through complex implementation challenges
- Champion automation, reliability, and engineering best practices throughout the data organization
- Thinks strategically while remaining execution-oriented, making pragmatic trade offs between speed, scalability, and technical debt
- Builds trust through transparency and strong communication, delegating to and developing future technical leaders
- Thrives in fast-moving, ambiguous environments and helps others navigate change

## Requirements
- 11+ years of experience in analytics engineering, business intelligence, data engineering, or related fields
- 3+ years managing high-performing technical teams, growing and developing people
- Deep expertise with SQL and modern analytics engineering practices
- Experience building analytics platforms using DBT, Snowflake, Airflow or similar orchestration tools
- Familiarity with Git and CI/CD workflows and BI platforms
- Strong understanding of dimensional modeling, semantic layers, and data warehousing concepts
- Experience defining data governance, testing, and data quality frameworks
- Excellent stakeholder management and communication skills
- Demonstrated ability to influence technical strategy across multiple organizations

## Nice to Have
- Experience partnering with accounting/close the books procedures at a public company
- Experience managing audit processes and governance programs is a plus
- Experience at a high-growth SaaS or technology company
- Experience scaling analytics organizations through rapid company growth
- Familiarity with event-driven data architectures and product analytics
- Experience supporting experimentation platforms and machine learning initiatives
- Knowledge of metrics governance and executive KPI frameworks

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