ES Data Ops Strategist

About the role

The ES Office of Data (ES OOD) is the strategic data foundation for Salesforce's Global Employee Success (ES) Operations. This role involves establishing and scaling the data foundations specifically for the HR Operations team.

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
• 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
• Translate Data Program Strategy and Ops roadmaps into automated technical solutions

Requirements

• 4–6 years of experience in data operations, data engineering, or a highly technical business intelligence role
• 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 via REST APIs
• Working knowledge of data privacy standards and PII handling practices (e.g., data masking, access controls)