Data Strategy Operations Manager

Abnormal

4h•$107,100 - $154,000

About The Position

The Data Strategy and Operations Manager at Abnormal AI owns the go-to-market data quality strategy and stewards data across Salesforce and connected systems. The role designs processes, controls, and intelligent workflows that keep data accurate, enriched, and trusted at scale, enabling Sales, Marketing, Customer Success, and Finance to provide executive leadership with reliable metrics. The manager determines where AI agents and automation should take over repetitive data work and where human judgment remains necessary. They partner with cross-functional teams to evaluate system changes affecting data programs, establish governance and quality practices, own enrichment strategy, and lead a portfolio of data quality and automation projects.

Requirements

At least 5 years of experience in Sales Operations, Data Operations, or a similar analytical or systems role.
Hands-on experience building automation with AI or LLM tools, such as agents, prompt-driven workflows, or AI-assisted enrichment, with shipped examples available to 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 Salesforce administrators.
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 controls are needed for privacy, security, and accuracy.
Detail-oriented, self-motivated, proactive, and quick to learn new tools.
Strong written and verbal communication skills, including the ability to explain technical and AI concepts to non-technical partners.

Nice To Haves

Experience with workflow automation or integration platforms such as Workato or Zapier.
Experience with modern data stack tools such as Snowflake or dbt.
SQL experience.
Experience at a high-growth SaaS or security company.

Responsibilities

Set the data governance strategy, standards, ownership model, and source-of-truth hierarchy for go-to-market data across Salesforce and connected systems.
Establish policies, access controls, and field-level definitions, including rules for record creation and deprecation, and monitor adherence.
Ensure data compliance and security, and flag risks to IT, security, and leadership.
Replace high-volume manual tasks—including deduplication, enrichment, account matching, hierarchy mapping, routing, and 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 appropriate owner, and fixes issues without human intervention where appropriate.
Evaluate and select AI, enrichment, and automation tools; run pilots; and measure impact through time saved, accuracy gains, and coverage.
Own the enrichment strategy and maintain accurate account firmographics, including hierarchies, employee count, location, industry, and Fortune ranking.
Serve as the subject matter expert for Business Operations, Marketing Operations, 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.