Data Quality Analyst (Salesforce Data Steward

About Us

Sophos is a cybersecurity leader defending 600,000 organizations globally with an AI-driven platform and expert-led services. Sophos meets organizations wherever they are in their security maturity and grows with them to defeat cyberattacks. Its solutions combine machine learning, automation, and real-time threat intelligence with frontline human expertise from Sophos X-Ops to deliver advanced, 24/7 threat monitoring, detection, and response.

Sophos offers industry-leading managed detection and response (MDR) alongside a comprehensive portfolio of cybersecurity technologies — including endpoint, network, email, and cloud security, extended detection and response (XDR), identity threat detection and response (ITDR), and next-gen SIEM. Together with expert advisory services, these capabilities help organizations proactively reduce risk and respond faster, with the visibility and scalability needed to stay ahead of evolving threats.

Sophos goes to market with a global partner ecosystem, including Managed Service Providers (MSPs), Managed Security Service Providers (MSSPs), resellers and distributors, marketplace integrations, and cyber risk partners, giving organizations the flexibility to choose trusted relationships when securing their business. Sophos is headquartered in Oxford, U.K. More information is available at

We are seeking a Data Quality Analyst (Salesforce Data Steward) to ensure the accuracy, completeness, and integrity of customer and account data within Salesforce. This role supports global Sales, Finance, and Operations teams by maintaining high-quality data standards, enabling reporting, and driving scalable, automated data processes.

Beyond traditional stewardship, this role is expected to leverage AI and automation to proactively validate data, surface and resolve exceptions before they cause problems, and ensure that data issues never block critical downstream revenue processes (Quote-to-Cash). The ideal candidate pairs deep Salesforce data expertise with a builder's mindset — someone who would rather automate a recurring validation than run it by hand every week.

Data Quality & Stewardship

• Salesforce data quality — Manage and improve data quality across core objects (Accounts, Contacts, Opportunities), ensuring completeness and accuracy of key firmographic fields such as industry, company size, geography, and DUNS.
• Enrichment & standardization — Execute data enrichment activities using third‑party providers and manual research; validate and standardize inbound data prior to updates.
• Cleansing at scale — Perform deduplication, cleansing, and bulk data updates using tools such as Demand Tools and Data Loader.
• Reporting & monitoring — Develop data quality reports and dashboards (Power BI / Salesforce) to monitor KPIs, track data health, and identify trends.
• Governance & compliance — Enforce data governance standards, maintain documentation and metadata, and ensure compliance with privacy and regulatory requirements.

AI & Automation for Data Validation

• Automated validation — Design, build, and maintain automated data‑validation checks that continuously monitor Salesforce data against business rules, catching errors and gaps in near real time rather than after the fact.
• Unblock downstream processes — Ensure data quality issues do not block or delay critical downstream revenue processes (Quote‑to‑Cash). Proactively detect, flag, and resolve records that would otherwise fail these processes, and build alerting so problems are caught before they stall the business.
• Apply AI / LLMs — Use AI and large language models to accelerate data validation, matching, classification, enrichment, and anomaly detection — for example, standardizing messy inbound data, identifying likely duplicates, or explaining why a record failed a rule.
• Build automation — Develop and maintain SQL / Python‑based data processing, validation pipelines, and automation; reduce manual data work through repeatable, self‑service, and scheduled processes.
• Partner with technical teams — Collaborate with technical and Rev Ops teams on integrations, workflows, and system design so that data quality…