Are You a Data Visionary Ready to Shape the Future of a Fast-Growing SaaS Company?

ServiceTitan is on a mission to revolutionize the trades industry, and we need a Data Governance Lead to be the driving force behind our data integrity. This isn't just a role about policies and procedures; it's about pioneering a new era of data excellence where AI and automation are at the core of our strategy.

You'll be the champion of our enterprise data assets, ensuring they are accurate, complete, and reliable. We're looking for someone who thrives on solving complex data puzzles and is ready to leverage cutting-edge tools and scripting to automate data quality checks and elevate our standards.

What You'll Do:

• Independently lead data governance initiatives, partnering with data engineers, data scientists, and business units to tackle data quality and governance challenges.

• Develop and maintain data dictionaries, data lineage, and data profiles.

• Champion data quality by conducting in-depth data analysis to investigate and diagnose the root causes of complex data quality issues.

• Mentor data quality analysts and serve as a subject matter expert, advocating for data quality and governance across the organization. This includes communicating risks, progress, and opportunities to both technical and non-technical stakeholders.

• Design, implement, and automate a robust data control framework, using AI tools and advanced techniques to create scalable solutions. This will include developing and implementing data quality checks, rules, and metrics while proactively identifying new validations to prevent issues before they arise, shifting our data management approach from reactive to proactive.

• Lead the entire process from creating Jira tickets for data quality issues to collaborating with cross-functional teams, ensuring issues are resolved with proper root cause analysis (RCA) and remediation plans.

• Identify and implement process improvements, encompassing workflows and tools. This self-starter role requires the ability to quickly identify an opportunity and execute on it without delay.

• Proactively identify and define new data validations and checks to prevent quality issues before they arise, shifting our approach from reactive to proactive data management.

• Take responsibility for data source identification, controls monitoring, and the overall data quality framework and management.

• Understand downstream impacts and effectively communicate data changes.

• Influence other teams to adopt data governance processes and procedures.

Required Skills:

• Bachelor's degree in Information Technology, Computer Science, or a related field. A Master's in Computer Science is a plus.

• 10+ years of experience in data governance and analytics.

• Strong practical experience with data governance and data quality management.

• Deep understanding of enterprise data ecosystems (SFDC, Workday, NetSuite etc.) and the ability to conduct hands-on data analysis.

• Proven expertise in SQL for data querying, analysis, and manipulation.

• Excellent problem-solving and critical thinking skills.

• Ability to distill complex data findings into actionable recommendations.

• Strong communication (verbal and written) and interpersonal skills, with the ability to explain complex technical concepts to non-technical audiences.

• Ability to collaborate effectively with cross-functional teams across multiple time zones.

• Strong understanding of data management concepts with hands-on experience using Snowflake.

• Familiarity with the Quote-to-Cash (Q2C) process.

• Demonstrated ability to identify, analyze, and resolve complex data quality issues, with strong attention to detail.

• Comfortable working under tight deadlines in a high-growth environment.

• Ability to leverage AI and machine learning tools to automate data quality monitoring, shifting the focus from manual checks to proactive, intelligent data management.

• Proven ability to work independently and as part of a team in a fast-paced, dynamic environment.

Preferred Skills:

• Understanding of various data domains and their specific data quality challenges (e.g., billing data, contracts data, financial data).

• Certifications in data management or data quality (e.g., CDMP) are a plus.

• Experience with scripting languages (e.g., Python) for data analysis and automation is a plus.

• Experience with data visualization tools (e.g., Tableau) to create data quality dashboards.