Sr. ES Data Management Specialist

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Job Category

Data

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword — it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

The ES (Employee Success) Global Operations team at Salesforce forms the operational core of our HR function, dedicated to ensuring a world-class employee experience. This team is responsible for delivering exceptional HR services across all regions, managing the essential processes and systems that enable our global talent to thrive.

As part of the ES Office of Data vision, the ES Data Management team drives the strategy and execution of our people data programs, ensuring the integrity and usability of information through robust data governance, quality, and metadata management. In this role, you will be responsible for documenting and maintaining data landscapes, as well as executing efficient frameworks to assess data quality, ensure compliance with data governance policies, and drive data literacy for accurate, AI-driven outcomes. This role will help advance the maturity of our ES data management capabilities across the organization.

Responsibilities

• Data Profiling and Monitoring : Proactively analyze ES data sources to identify quality issues, inconsistencies, and anomalies. Develop and maintain data quality dashboards and scorecards to monitor the health of critical data elements (CDEs) over time.
• Root Cause Analysis : Investigate the source of data quality errors, working across ES and IT / DET to understand process or system breakdowns. Recommend and help implement solutions to prevent future issues.
• Data Cleansing and Remediation : Lead and coordinate data cleansing initiatives, defining the logic for corrections and working with Data Stewards / Process Owners to execute cleanup efforts.
• Rule and Standard Development : Define and document data quality rules and standards for key ES data domains (e.g., employee master data, compensation, recruiting). Ensure these standards are embedded in business processes and systems.
• Business Glossary and Data Dictionary : Own and maintain the central ES business glossary and data dictionaries. Define and document key business terms, metrics, and data elements to create a common language for all HR data stakeholders.
• Data Lineage and Traceability : Document the end-to-end flow of ES data, from its source systems to its downstream consumption to ensure transparency and build trust in data.
• Metadata Governance : Classify ES data according to its sensitivity and usage. Ensure that metadata is consistently captured, maintained, and accessible to authorized users.
• Partnership : Partner closely with the ES Ops team to identify the root cause of transactional data errors and recommend process improvements at the point of data entry to enhance accuracy and efficiency.
• Collaboration : Collaborate with COEs (e.g., Talent Acquisition, Compensation, Talent Management) to define and validate critical data elements, establish quality thresholds for their domains, and ensure their reporting and analytics needs are met with trusted data.
• Data Engineering : Design, build, and maintain data pipelines to extract and consolidate ES Ops data from diverse sources (ex : HRIS, case management systems) into Data platforms like Snowflake / AWS / Data Cloud.
• Develop complex transformations using SQL and / or Python to clean, aggregate, and model raw data into analysis-ready datasets specifically structured to power the ES Ops 360 dashboard.
• Lead small to medium-sized projects related to data quality improvement or metadata implementation. Develop project plans, manage timelines, and report on progress.
• Define key data quality metrics and indicators and facilitate the development and implementation of supporting standards.

Qualifications

Unleash Your Potential

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what's possible — for yourself, for AI, and the world.

Accommodations

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Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights : workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Skills Required

Data Profiling, data engineering , Data Cleansing, Data Governance, Tableau, Python, Sql