Job Description
Ready to be a Titan?
ServiceTitan is looking for an extraordinary Data Quality Analyst to play a critical role in ensuring the accuracy, completeness, consistency, and reliability of our enterprise data assets. This individual will support efforts to define, implement, and monitor data quality standards and processes across various data domains. The Data Analyst will work closely with data owners, data stewards, data consumers, and business stakeholders to identify data quality issues, determine root causes, recommend solutions, and track the remediation of identified problems. The Data Quality Analyst will report directly to the Director of Data Governance.
This role requires a blend of strong analytical skills, technical proficiency, attention to detail, and excellent communication to support a data quality culture within the organization.
What You'll Do:
Perform in-depth data profiling and analysis to identify data quality issues, anomalies, and inconsistencies.
Develop and implement data quality checks, rules, and metrics using appropriate tools and techniques.
Automate data quality checks and reporting where feasible to enhance efficiency and scalability.
Create and maintain data quality dashboards and reports to monitor data health and track improvements over time.
Investigate and diagnose the root causes of complex data quality issues. Create Jira tickets and work collaboratively with cross-functional teams to make sure issues are resolved with proper RCA and remediation plans.
Identify opportunities to improve data quality processes, workflows, and tools.
Communicate data quality issues, risks, and progress to technical and non-technical stakeholders.
Act as a subject matter expert and advocate for data quality within the organization.
Proactively identify new data validations/checks to improve data quality.
Required Skills:
Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, or a related quantitative field.
5+ years of experience as data quality analyst.
Strong SQL expertise for data querying, analysis, and manipulation.
Experience using Salesforce (SFDC) and a solid understanding of how to analyze and fix data quality problems in SFDC. This role involves working with our core enterprise systems, such as Workday and SFDC, to ensure data accuracy and integrity.
Expertise in articulating data issues with different audiences i.e. business/technical/functional stakeholders.
Familiarity with the Quote-to-Cash (Q2C) process.
Experience with data warehouses (Snowflake preferred).
Demonstrated ability to identify, analyze, and resolve complex data quality issues; Strong attention to detail
Comfortable with tight deadlines in a high-growth environment.
Solid understanding of data management concepts and database technologies.
Excellent analytical, problem-solving, and critical thinking skills.
Strong communication (verbal and written) and interpersonal skills, with the ability to explain complex technical concepts to non-technical audiences.
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).
Certification in data management or data quality (e.g., CDMP) is a plus.
Experience with scripting languages (e.g., Python) for data analysis and automation is a plus.
Experience with data profiling and data quality tools (e.g., Collibra, Monte Carlo, etc.).
Experience leveraging AI/LLMs to enhance efficiency in data analysis, anomaly detection, and data validation.
Be Human With Us:
Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re solving. We’re in this together. Come be human, with us.
Use of AI Technology:
We use technology, including automated and AI-assisted tools, to support certain aspects of our recruitment process. These tools are designed to improve efficiency and enhance the candidate experience. AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams.