ES Data Ops Strategist

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Job Category

Employee Success

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.

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.

Position Summary
The ES Office of Data (ES OOD) is the strategic data foundation for Salesforce's Global Employee Success (ES) Operations — championing trusted employee data, unified governance, HRIS security, and AI-ready data foundations that power seamless, intelligent hire-to-retire experiences.
We are seeking a self-driven ES Data Ops Engineer & Strategist within the ES Office of Data — to establish and scale the data foundations specifically for our HR Operations team. This is a unique role designed for a data professional who loves building foundational structures, automating quality checks, and driving operational excellence.

Key Responsibilities

* Reimagine, design, and build the data models needed to track next-generation HR service delivery, owning backend pipelines for operational KPIs such as case management lifecycles, CSAT, escalation rates, severity distributions, and Cost to Serve
* Design and implement local data models, schemas, and staging areas tailored for agile HR Operations reporting and insights
* Develop and maintain operational data pipelines using clean, production-grade SQL and Python to apply HR business logic and transform raw data into action-ready datasets
* Build and support secure data connections, webhooks, and APIs to sync operational data across internal HR platforms and tools (e.g., ticketing systems, HRIS)
* Transition the team from reactive manual auditing to proactive, automated continuous monitoring — designing and deploying data quality scripts and scheduled test suites that instantly flag anomalies, missing fields, or logic violations in incoming HR operational data
* Maintain, monitor, and optimize HR data pipelines and workflows — proactively identifying bottlenecks, automating manual steps, and establishing rigorous SLAs for data freshness and uptime
* Enforce strict data security boundaries, ensuring localized operational data views comply with global PII regulations, data masking standards, and confidentiality protocols
* Partner closely with the core HR Data Product Engineering team to align with broader corporate data architectures, ensure governance compliance, and smoothly ingest upstream core datasets
* Act as the technical bridge across the ES Office of Data pillars—collaborating with Data Governance to embed security rules into pipelines, engineering the high-performance upstream data layers that fuel HRIS Reporting, and translating Data Program Strategy and Ops roadmaps into automated technical solutions.

Required Skills & Experience

* 4–6 years of experience in data operations, data engineering, or a highly technical business intelligence role
* Experience modeling complex operational workflows (e.g., ticketing, customer support, case management) into structured analytics tables
* Proven experience building data validation, monitoring, and automated testing setups (e.g., dbt tests or custom Python validation scripts)
* Strong SQL and Python proficiency for automated workflows and data transformations
* Solid understanding of data schemas, dimensional modeling, and structuring data for high-performance operational reporting
* Familiarity with cloud data platforms (e.g., Snowflake, BigQuery), orchestration tools (e.g., Airflow), and integrating data