Lead, manage and influence a team of 4-5 within the "Sales Data Quality" team and own strategy, execution, and enablement for innovative data solutions and enrichment projects across multiple business segments and domains.
Develop and implement scalable, automated processes for validating complex business structures (e.g., CFS, corporate hierarchies, parent/child relationships).
Lead and manage the delivery of stakeholder project requests, including advanced data searches and account segmentation.
Architect and oversee data quality pipelines—including automated validation, anomaly detection, and proactive identification of gaps using Python, SQL, and AI/ML tools (e.g., LLM agents, Cortex AI).
Establish and maintain account and contact scoring frameworks to track data completeness and accuracy; publish dashboards and reports to enable business decisions.
Drive adoption of AI tools and develop internal agents for advanced data quality management and business enablement.
Mentor, coach, and develop cross-disciplinary team members; champion a culture of innovation, excellence, and continuous improvement.
Serve as the primary escalation point for complex data quality and enrichment issues; design frameworks, documentation, and training for scalable data stewardship.
Collaborate with data engineers, sales ops, and analysts to optimize data pipelines and business impact.
Translate complex data problems and insights into actionable business strategies and operational improvements.
Requirements
2+ years of people management experience within "Sales Data Quality/Sales Ops"
7+ years of relevant sales data quality experience at a high growth SaaS
Deep expertise in SQL, Python, and modern AI/ML techniques for data enrichment, validation, anomaly detection, and automated agent development.
Proven success architecting and scaling innovative, automated data quality solutions for large, cross-functional teams.
Track record of leadership in data analytics, business enablement, and cross-functional collaboration.
Strong experience with cloud-based data platforms (e.g., Snowflake), ETL/ELT tools (Fivetran, Airflow), and data modeling for complex business environments.
Knowledge and experience in building, deploying, and managing AI agents and their application to business data problems.
Familiarity with CRM systems (e.g., Salesforce), dashboard/reporting tools (e.g., Tableau), and collaborative documentation platforms (e.g., Seismic, Confluence).
Exceptional communication skills: able to explain complex technical issues to non-technical stakeholders and drive adoption.
Demonstrated business impact and process improvement via advanced analytics and data quality initiatives. Experience with LLMs or generative AI in data QA is a plus.
Strong project management, mentoring, and stakeholder engagement abilities.
Benefits
Health insurance
Pharmacy benefits
Optical care
Dental care
Paid time off
Sick time off
Short term disability coverage
Long term disability coverage
Life insurance
401k contribution
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