Who is Flock?

Flock Safety is the leading safety technology platform, helping communities thrive by taking a proactive approach to crime prevention and security. Our hardware and software suite connects cities, law enforcement, businesses, schools, and neighborhoods in a nationwide public-private safety network. Trusted by over 5,000 communities, 4,500 law enforcement agencies, and 1,000 businesses, Flock delivers real-time intelligence while prioritizing privacy and responsible innovation.

We’re a high-performance, low-ego team driven by urgency, collaboration, and bold thinking. Working at Flock means tackling big challenges, moving fast, and continuously improving. It’s intense but deeply rewarding for those who want to make an impact.

With nearly $700M in venture funding and a $7.5B valuation, we’re scaling intentionally and seeking top talent to help build the impossible. If you value teamwork, ownership, and solving tough problems, Flock could be the place for you.

The Opportunity

Flock is seeking a Director of Data Analytics to lead our analytics organization across Analytics Engineering and the Analytics Data Platform. This role will manage teams responsible for building trusted, analysis-ready data assets, standardized metrics, and self-service analytics that support decision-making across the entire company, including Revenue, Finance, Customer Success, Marketing, Product, and Operations.

This leader will own analytics strategy, technical standards, and delivery execution while acting as a partner to stakeholders – driving prioritization, tradeoffs, and escalation as analytics demand scales with the business. We’re looking for a deeply hands-on technical leader who can set strategy and actively contribute — building dbt models, writing SQL, reviewing PR’s, and debugging data issues alongside the team.

What You’ll Lead

You will manage teams responsible for the following, and we expect you to be hands on here:

• Build and maintain core dbt data models that transform raw data into trusted analytics assets

• Implement and operate semantic layers to standardize metric definitions across the company

• Own data quality and reliability, including testing, monitoring, and alerting

• Enable self-service analytics through governed BI tools (Sigma) and discoverable data models

• Partner deeply with Revenue, Finance, Customer Success, Marketing, Product, and Ops

• Operate with an analytics-as-code mindset, leveraging Redshift/Snowflake, dbt, SQL, and Git.

• Your role is to ensure this work scales sustainably and delivers measurable business impact.

Key Responsibilities

• Strategy & Direction:

  • Define and own the analytics vision and roadmap, balancing short-term stakeholder needs with long-term platform investments

• Technical & Platform Leadership:

  • Serve as a technical escalation point for complex modeling, performance, and metric definition challenges

  • Set standards for dbt modeling, semantic layers, data testing, documentation, and analytics CI/CD

  • Oversee the Analytics Data Platform to ensure reliability, performance, and cost efficiency

  • Partner with Data Engineering on warehouse architecture, orchestration, and observability

• Stakeholder Partnership & Prioritization

  • Serve as the primary analytics leader for senior stakeholders across the business, translating key business needs into actionable next steps for the team

  • Own prioritization of initiatives and sequencing of work

  • Clearly communicate tradeoffs, capacity constraints, and risks, escalating when needed

• Metrics, Governance & Trust

  • Own core business, revenue, and financial metric definitions

  • Establish governance that ensures consistency without slowing delivery

  • Champion single sources of truth while enabling broad, safe access to data

• People Leadership

  • Lead and grow managers and senior ICs across Analytics Engineering and the Analytics Data Platform team

  • Foster a culture of ownership, quality, and continuous improvement by leading from the front — pairing with ICs, reviewing work, and modeling high technical standards