IT Data Analyst, Salesforce

Evolv Technologies Holdings•Waltham, MA

1d•Hybrid

About The Position

Evolv is seeking a technically sharp, data-obsessed analyst and integration builder to join their data infrastructure team. This role focuses on the deep data layer, partnering with Salesforce admins to own pricebook architecture, data integrations, the Snowflake data warehouse, and AI-powered automation and analytics. The ideal candidate is passionate about data, enjoys solving complex data problems, and is skilled in connecting Salesforce, modern data infrastructure, and applied AI to optimize business operations and drive insights.

Requirements

4+ years of hands-on experience working with Salesforce data, reporting, and integrations in a production environment.
Deep fluency with Salesforce data: reports, dashboards, SOQL, Data Loader, data quality management, and pricebook/product catalog architecture.
Demonstrated experience building and maintaining data integrations between Salesforce and external systems (REST/SOAP API experience; middleware platform experience a plus).
Strong SQL skills and experience working with a modern data warehouse (Snowflake strongly preferred).
Hands-on experience with AI integration development: building workflows, automations, or pipelines that incorporate LLM APIs, AI services, or machine learning outputs.
Experience with Salesforce CPQ and/or Revenue Cloud Advanced, with specific emphasis on pricebook structures and data flows.
Genuine passion for data: you think in queries, you build things that surface insight, and you are bothered by data that is wrong or incomplete.
Strong analytical and problem-solving skills; comfort working independently on ambiguous, cross-functional data problems.
Salesforce Administrator certification (ADM-01 or equivalent) required.

Nice To Haves

Salesforce CPQ Specialist and/or Revenue Cloud certification.
Experience with Snowflake-specific features: dbt, Streams, Tasks, or data sharing.
Familiarity with Salesforce Einstein Analytics / Tableau CRM or similar BI tools connected to Salesforce.
Experience with integration middleware platforms (MuleSoft, Boomi, Workato, or similar).
Experience building AI-powered automations using OpenAI, Anthropic, Google Gemini, or comparable LLM APIs.
Exposure to Salesforce Service Cloud administration or configuration.
Experience in a SaaS or technology company with a direct enterprise sales motion and subscription/recurring revenue model.
Familiarity with revenue recognition principles (ASC 606) and how they intersect with CPQ and billing configuration.

Responsibilities

Own the Salesforce data layer, including pricebook architecture, product catalog data, data quality, and advanced configuration.
Design and maintain pricebook structures in Salesforce CPQ to support accurate quoting, contract generation, and revenue recognition.
Establish and enforce Salesforce data standards, including field governance, deduplication logic, validation rules, and data hygiene processes.
Perform data analysis within Salesforce to identify anomalies, inconsistencies, and trends impacting sales and revenue reporting.
Build and maintain advanced Salesforce reports and dashboards for leadership and operators.
Own the architecture and health of data integrations between Salesforce and downstream/upstream systems, including Snowflake, ERP, and billing platforms.
Design, build, and maintain reliable data pipelines from Salesforce to Snowflake for analytics, reporting, and AI workloads.
Troubleshoot integration failures, data sync delays, and field-mapping errors, implementing permanent fixes and monitoring.
Maintain a well-documented integration architecture, including data dictionaries, field mappings, transformation logic, and pipeline diagrams.
Partner with IT and Data Engineering to ensure data flows are secure, auditable, and compliant with data governance standards.
Write and maintain SQL/Snowflake queries for reporting, data validation, and ad-hoc business analysis.
Identify, scope, and build AI-powered integrations and automations to reduce manual work and improve decision-making.
Develop AI-assisted workflows within and around Salesforce using LLM APIs, Salesforce Einstein, or third-party AI tools.
Build automations that connect Salesforce data with AI models and surface outputs back into business workflows.
Evaluate emerging AI and automation tools and make practical recommendations for adoption.
Ensure AI-driven workflows are implemented with appropriate data governance, auditability, and security.
Design and build advanced reporting solutions pulling from Snowflake, Salesforce, and other data sources.
Support leadership with ad-hoc data queries, analysis, and modeling for forecasting and reporting.
Build self-service reporting and analytics capabilities.
Develop and maintain data models in Snowflake for reliable reporting.
Collaborate with Salesforce admins on platform decisions impacting data and integrations.
Serve as the technical escalation point for Salesforce data and integration issues.
Provide technical input on Salesforce platform decisions with downstream data or integration implications.