Operations Data Manager

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DataData Manager

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Quick Summary

Key Responsibilities

Lead the Operations Analytics Capability Establish and evolve the team’s operating model, including intake, prioritization, and delivery rhythms across the core teams.

Requirements Summary

3+ years of experience in Data Analytics, Business Intelligence, Operations Analytics, Strategy, Consulting, or a related field. 1+ years of experience leading, coaching,

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DataData Manager

About the Role:

Operations teams sit on some of the richest data in the company. Every fraud decision, support interaction, partner implementation, and receipt review generates signals about how Fetch is performing and where users and internal teams run into friction. The challenge isn’t collecting that data, it’s making sure it consistently shapes operational decisions.

The Operations Data Manager leads the team that turns operational data into insight and action. Reporting to the SVP of Operations, this role leads Fetch’s centralized Operations Analytics team, partnering with leaders across Ad Operations, AI Operations, Platform Integrity, and User Support to define KPIs, build trusted reporting, and surface the trends and anomalies that drive strategy, prioritization, and process improvement.

This is more than a people-management role, it is an opportunity to shape how Operations uses data. You will set the team’s operating model, lead and develop a team of Operations Data Analysts, and build the standards and partnerships that make operational analytics a trusted input into decisions. Success is measured by the decisions your team influences, the operational friction your team helps eliminate, and the measurable business outcomes your work supports.

This is a full-time role that can be held from one of our US offices or remotely in the United States.

Role Responsibilities:

Lead the Operations Analytics Capability

Establish and evolve the team’s operating model, including intake, prioritization, and delivery rhythms across the core teams.
Define team standards for analysis quality, KPI definitions, dashboard design, documentation, and knowledge management.
Own intake and prioritization of analytics requests, balancing ad-hoc needs with longer-term strategic work and setting clear expectations with stakeholders.
Build repeatable mechanisms that turn operational data into prioritized recommendations supported by measurable business impact.

Lead & Develop a High-Performing Team

Hire, onboard, coach, and develop a team of Operations Data Analysts.
Create clear goals, quality standards, and development plans for each analyst.
Review the team’s SQL, analyses, and deliverables to ensure accuracy, clarity, and actionable recommendations.
Foster a culture of curiosity, analytical rigor, accountability, and continuous improvement.

Partner with Operational Leaders

Partner closely with Operations leaders to understand data needs, define and track KPIs, and design reporting solutions.
Provide insights that inform operational strategy, process improvements, staffing and capacity planning, and day-to-day decision-making.
Communicate findings, trends, and recommendations to cross-functional and senior stakeholders through clear visuals and compelling narratives.
Stay hands-on where needed, contributing to complex analyses and work with new or unstructured data sources.

Ensure Trusted, Scalable Reporting

Oversee dashboards and reporting in Hex, Tableau and Grafana, promoting self-service, consistent metric definitions, and early detection of anomalies.
Work with engineering to ensure data quality and reliability, and to scope and prioritize automated data tables and pipelines.
Maintain documentation and team workflows in Confluence, Jira, and Bitbucket so work is repeatable, transparent, and easy to hand off.

Measure Operational Outcomes

Define success metrics that connect operational improvements to business outcomes.
Evaluate whether process changes and initiatives delivered their intended results, and close the loop to improve future decisions.

Minimum Requirements:

3+ years of experience in Data Analytics, Business Intelligence, Operations Analytics, Strategy, Consulting, or a related field.
1+ years of experience leading, coaching, and developing analysts or other high-performing teams.
Demonstrated success building team capabilities, standards, or operating models from concept to execution.
Strong SQL skills, with the ability to extract, manipulate, and understand large datasets across multiple domains and to review and guide the work of others.
Experience with Snowflake and familiarity with cloud-based data warehousing solutions.
Experienced with HEX, Tableau or Grafana, with the ability to set standards for intuitive dashboards that communicate insights, enable self-service, and surface anomalies.
Proven ability to synthesize ambiguous or unstructured data with business context to drive strategic recommendations.
Strong communication, facilitation, and stakeholder management skills with senior stakeholders, including defining KPIs and reporting solutions.
Ability to prioritize and manage multiple competing projects and requests, for yourself and for a team.
Knowledge of the Atlassian suite, including Bitbucket, Confluence, and Jira.

Preferred Requirements:

Experience in consumer technology, fintech, marketplace, or high-growth digital businesses.
Experience leading analytics for fraud, customer support, or other operational functions.
Experience creating automated data tables using dbt and Airflow, and building data pipelines and ETL processes.
Experience using Python to generate insights.
Experience leveraging AI and automation to improve insight generation and operational effectiveness.

What Success Looks Like:

Within your first 12 months, you will:

Establish Operations data as a trusted source of insight for AdOps, AIOps, Platform Integrity and User Support.
Build a high-performing team with clear operating standards, quality bar, and scalable processes.
Create a repeatable intake and prioritization model that balances ad-hoc requests with strategic work.
Align stakeholders on consistent KPI definitions and trusted, self-service dashboards.
Partner with data engineering to improve data reliability and automate recurring reporting.
Influence operational decisions with evidence-based recommendations tied to measurable outcomes.

Compensation:

At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $135,044 to $158,875. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.