Data Strategy Operations Manager

Abnormal · Remote - USA · Data

Posted 2026-11-06

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About the Role

As the Data Strategy and Operations Manager at Abnormal AI, you will own our go-to-market data quality strategy and serve as the steward of data across Salesforce and the systems around it. You will design the processes, controls, and intelligent workflows that keep data accurate, enriched, and trusted at scale, so Sales, Marketing, Customer Success, and Finance can give executive leadership reliable metrics. You will decide where AI agents and automation take over repetitive data work and where human judgment still matters, and partner with cross-functional teams to evaluate system changes that affect our data programs.

Who you are

Data obsessed and just as obsessed with removing manual work, with a habit of automating any process that relies on fixing records by hand

Curious about AI and a daily user, with experience shipping workflows with LLMs, agents, or AI-assisted tooling, and able to tell a useful application from a demo

Eager to build and shape a program rather than only maintain one, and able to create systems that hold up at global scale

Highly analytical, able to see the big picture and spot trends and gaps, then zoom in with practical, specific recommendations

Steady when juggling multiple priorities in a constantly changing environment

A good teammate, dedicated to the mission, who likes to have fun along the way

What you will do

Set the data governance strategy, standards, ownership model, and source-of-truth hierarchy for GTM data across Salesforce and connected systems

Establish policies, access controls, and field-level definitions, including record creation and deprecation rules, and monitor adherence

Ensure compliance and security of our data, and flag risks to IT, security, and leadership

Replace high-volume manual tasks (deduplication, enrichment, account matching, hierarchy mapping, routing, anomaly review) with automated and AI-assisted workflows

Design and maintain AI agents and LLM-powered workflows that classify, enrich, validate, and remediate data, with guardrails, human review points, and accuracy measurement

Build automated data quality monitoring that detects issues early, alerts the right owner, and fixes them without human intervention where appropriate

Evaluate and select AI, enrichment, and automation tooling, run pilots, and measure impact through time saved, accuracy gains, and coverage

Own the enrichment strategy and keep account firmographics accurate: hierarchies, employee count, location, industry, and Fortune ranking

Act as the subject matter expert for Business Ops, Marketing Ops, Customer Success, and Finance, run a defined feedback intake process, and support consistent reporting and dashboards

Manage a portfolio of data quality and automation projects with clear priorities, owners, and outcomes

Must Haves

5+ years in Sales Operations, Data Operations, or a similar analytical or systems role

Hands-on experience building automation with AI or LLM tools (agents, prompt-driven workflows, AI-assisted enrichment), with shipped examples you can easily share

Strong understanding of data lifecycle management, data modeling, master data management, and requirements gathering

Demonstrated understanding of Salesforce automation, including Flow and validation rules, and experience working closely with admins

Experience implementing and managing data and enrichment tools, including AI-native tools such as Clay, Kernel, Starbridge, and Onfire

Proficiency in Excel

Track record of leading data management projects from idea to result

Sound judgment about where AI is reliable and where it needs controls for privacy, security, and accuracy

Detail oriented, self-motivated, proactive, and quick to learn new tools

Strong written and verbal communication skills, including explaining technical and AI concepts to non-technical partners

Preferred: experience with workflow automation or integration platforms (such as Workato or Zapier), modern data stack tools (such as Snowflake or dbt), SQL, and a high-growth SaaS or security company

#LI-EM3

Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.

In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.

Base salary range:

$107,100—$154,000 USD

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