Data Quality Analyst (Salesforce Data Steward)

Team: Analyst

Location: India

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Manage and improve Salesforce data quality across core objects including Accounts, Contacts, and Opportunities, with a focus on key firmographic information such as industry, company size, geography, and DUNS.
• Perform data enrichment, standardization, cleansing, deduplication, and large-scale data updates using third-party enrichment providers, manual research, DemandTools, Data Loader, and similar solutions.
• Validate and standardize inbound data before updates to ensure consistency with established business and governance standards.
• Develop and maintain data quality reports and dashboards using Salesforce and Power BI to monitor KPIs, identify trends, and provide visibility into overall data health.
• Establish and enforce data governance standards, documentation, metadata practices, privacy requirements, and data-quality controls.
• Design and maintain automated validation checks that continuously evaluate Salesforce data against defined business rules and identify errors or gaps proactively.
• Monitor and resolve data-quality issues that could delay or block critical Quote-to-Cash processes, including building alerts that surface problems before they affect downstream operations.
• Apply AI and large language models to accelerate data matching, classification, enrichment, anomaly detection, standardization, and validation activities.
• Build and maintain SQL- and Python-based data processing, validation, and automation pipelines that reduce repetitive manual work.
• Partner with technical and Revenue Operations teams to improve integrations, workflows, system design, and upstream data controls.
• Measure the effectiveness of automation and continuously expand validation coverage across fields, objects, and business rules.
• Identify opportunities to improve data processes, operational efficiency, and scalability through automation and technology.

Requirements

• 4+ years of strong, hands-on experience managing Salesforce data and working with Salesforce data models.
• Proficiency in SQL and Python for data analysis, processing, validation, and automation.
• Hands-on experience creating automated data-quality checks and translating business rules into reliable validation logic.
• Experience applying AI or automation to data-related activities, such as matching, classification, enrichment, anomaly detection, or data validation, or a strong demonstrated interest in developing these capabilities.
• Practical experience with DemandTools or comparable tools for data transformation, cleansing, and deduplication.
• Experience with Power BI or Microsoft Power Platform, along with intermediate to advanced Excel skills.
• Proven experience managing large-scale datasets, data cleansing, deduplication, standardization, and quality improvement initiatives.
• Strong analytical and problem-solving abilities, exceptional attention to detail, and a proactive mindset toward automating repetitive processes.
• Understanding of Quote-to-Cash or order management processes and the impact that poor data quality can have on quoting, approvals, ordering, provisioning, and billing is advantageous.
• Experience with Dun & Bradstreet or other data enrichment providers is a plus.
• Familiarity with Salesforce APIs, SOQL, integrations, and workflow automation is preferred.
• Experience with Snowflake or other cloud data platforms is beneficial.
• Understanding of data governance frameworks and master data management concepts is advantageous.
• Experience with AI/LLM tools or frameworks applied to data quality and process automation is a plus.
• Salesforce certifications are considered an advantage.
• Strong communication and collaboration skills, with the ability to work effectively across business and technical teams.

Benefits

• Remote-first working environment with flexibility for eligible employees.
• Opportunity to work on data quality, automation, AI, and Salesforce initiatives with significant business impact.
• Collaborative and inclusive culture that values diverse perspectives and innovative thinking.
• Opportunities to build expertise through exposure to modern data, AI, analytics, and automation technologies.
• Employee-led diversity and inclusion networks that foster community, education, and advocacy.
• Annual charity, fundraising, and employee volunteer initiatives.
• Global sustainability initiatives supporting environmental responsibility.
• Global fitness and trivia activities designed to encourage connection and wellbeing.
• Dedicated wellbeing days and regular wellbeing webinars and training.
• Supportive environment focused on professional development, inclusion, and continuous improvement.