Description
The Q3 team within TabNext empowers engineering teams to deliver high-quality, reliable products that consistently meet or exceed customer expectations. Acting as "Quality Champions," we cultivate a quality-conscious development environment focused on the prevention, early detection, and rapid remediation of defects and product quality gaps. By driving engineering excellence through robust self-serve test automation, the curation of datasets and golden datasets, and advocating for the customer through comprehensive, end-to-end testing of complex business scenarios, we ensure a seamless and reliable user experience across the platform.
As a Data Analytics Lead at Salesforce, you are the guardian of data integrity. Beyond traditional BI, you will own the "Golden Dataset" lifecycle, creating the foundational truth used to validate and stress-test emerging products. You will ensure that as Salesforce innovates—from Agentforce to new Tableau Next features—our product teams are building on a bedrock of high-fidelity, governed data.
Key Responsibilities
Golden Dataset Ownership: Architect, build, and maintain the "Golden Dataset" lifecycle. This includes defining the source of truth, managing data lineage, and ensuring high-availability for product testing and executive reporting.
Emerging Product Validation: Partner with Product Management (PM) and Engineering to use golden datasets as the benchmark for validating new features. You will define the "success" metrics for alpha/beta products before they hit the general market.
Data Lifecycle Management: Lead the end-to-end lifecycle of data assets—from initial ingestion and cleansing to sunsetting obsolete schemas—ensuring zero "data drift" during rapid product iterations.
Required Skills & Experience
Experience: 7+ years in data analytics or data engineering, with a heavy focus on Data Governance or Data Quality (DQ) frameworks.
Golden Dataset Expertise: Proven track record of managing master data management (MDM) or "Golden Record" projects in a cloud-scale environment.
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Technical Stack:
Expert: SQL, Snowflake, and Data Cloud (Salesforce CDP).
Validation Tools: Experience with UAT (User Acceptance Testing) frameworks and A/B testing methodology for software products.
Visualization: Expert-level Tableau/CRMA for communicating data health and product readiness.
The "Detective" Mindset: A relentless focus on data quality—you are the person who finds the "needle in the haystack" that could break a product launch.
A related technical degree required.
Preferred Qualifications
Experience with AI/ML Validation: Using golden datasets to tune and validate Large Language Models (LLMs) or autonomous agents.
Experience with Salesforce Sales/Service/Marketing clouds or Industries cloud
Salesforce Certifications: Salesforce Data Cloud Consultant or Platform App Builder.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.