GTM Analytics Engineer

Posted 5 Days Ago
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Barcelona, Cataluña, ESP
Hybrid
Mid level
Big Data • Software
The Role
Design, implement, and maintain GTM data infrastructure and pipelines using dbt and cloud warehouses. Build BDM tables, enforce data quality and governance, integrate Salesforce, create semantic layers for analytics and AI, monitor pipeline performance, and collaborate with stakeholders to deliver curated datasets and AI-enabled analytics.
Summary Generated by Built In

The Role

The GTM Analytics Engineer designs, implements, and maintains scalable data infrastructure to enable analytics and reporting. Responsibilities center on the development, management, and governance of GTM (Finance, Marketing, Sales, CS) BDM Data architecture, GTM pipeline integration, data quality assurance, and the secure operation of BI tools across the GTM organization. This role reports to the Director of Revenue Operations.

 

What You’ll Be Doing

GTM Data Infrastructure & Pipeline Development

  • Manage all data models in dbt using version control (Git/GitHub), with pull-request review, automated testing, and CI/CD deployment pipelines.

  • Write and maintain dbt tests (schema, data, and unit tests) and enforce them in CI to catch regressions before they reach production.

  • Use AI-assisted development tools (e.g., Cursor, Claude) to accelerate modeling, refactoring, code review, and documentation.

  • Establish and enforce data modeling standards, including naming conventions and calculation methodologies

  • Design and optimize Business Dimensional Model (BDM) tables aligned with business requirements in dbt.

  • Develop, automate, and maintain GTM data pipelines, ensuring delivery for business analytics

  • Build and maintain reusable semantic layers with standardized metric definitions and business logic and YML files.

  • Perform user acceptance testing and continuously refine pipelines for performance and scalability

Data Governance and Pipeline Performance

  • Establish data quality controls (audits, logging, root cause analysis, automated cleansing) to ensure accuracy, reliability, and compliance throughout all data flows.

  • Implement monitoring and alerting for data pipeline performance (timing, error rates, duplication), maintaining SLAs, and proactive issue resolution.

  • Govern access and controls for sensitive customer, marketing, and product data, ensuring compliance with privacy regulations and security standards.

Collaboration & Documentation

  • Partner with analysts, data scientists, and stakeholders to deliver curated datasets, communicate data limitations, and support ad hoc data requests.

  • Maintain comprehensive documentation, including lineage tables, schema definitions, performance logs, and operational procedures for BDM and GTM solutions.

AI Solutioning and Management

  • Design and maintain AI-ready data models and semantic definitions that let LLMs query GTM data accurately and safely.

  • Integrate warehouse data into AI tools (e.g., Claude via MCP) to enable natural-language analytics, reducing reliance on static dashboards.

  • Build and maintain reusable AI skills, prompts, and agents that automate recurring analytics and data-ops tasks.

  • Partner with stakeholders to identify workflows where AI can replace manual reporting, and prototype/ship those solutions.

  • Establish guardrails, evaluation, and governance for AI-driven data access (scope, accuracy, sensitive-data handling).

Qualifications

Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role but your past experience doesn't perfectly align with the qualifications above, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

Required

  • Proficiency with data pipeline development, SQL, and cloud data warehousing (Snowflake, BigQuery, Redshift, etc.), including ingesting and transforming Salesforce data via APIs or native connectors.

  • Strong dbt experience — modeling, testing, and managing projects in a version-controlled, CI/CD workflow (Git/GitHub).

  • Proficiency with AI-assisted development and analytics tools (e.g., Cursor, Claude/LLMs) and interest in AI-native data workflows.

  • Familiarity with integrating data warehouses into AI/LLM tooling (e.g., MCP, semantic layers for AI consumption) — a strong plus.

  • Experience designing and managing Business Data Models (BDM) for data warehouse environments, incorporating Salesforce objects (Accounts, Opportunities, Campaigns) for analytics and reporting.

  • Hands-on experience with Salesforce data management, including SOQL, schema understanding, and troubleshooting sync issues.

  • Strong communication and collaboration skills, with the ability to partner with Sales, Marketing, and RevOps teams.

Location: Barcelona, Spain

For this role, we're embracing a hub-hybrid model, designed to balance flexibility with meaningful in-person collaboration. Team members in-office 2-days per week. We believe great things happen when people come together intentionally to connect, create, and build momentum as a team.

What you'll enjoy at Affinity:

  • We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.

  • Health Benefits: Comprehensive health insurance for both you and your family.

  • Learning & Development: We provide an annual education budget and a comprehensive L&D program.

  • Wellness Support: We provide a monthly budget for wellness memberships/equipment to support your overall health and happiness.

About Affinity

Affinity is the AI-first CRM for private capital, helping firms turn relationship intelligence into action across the investment lifecycle. Built on a decade of proprietary relationship, interaction and deal data, Affinity automatically captures activity, maps firm networks, and surfaces the connections and insights that help investors source, evaluate and win opportunities.

Trusted by more than 3,300 private capital firms, including 40% of the venture capital market and more than 330 private equity buyout teams, Affinity powers one of the industry's deepest relationship graphs. The platform is built on more than 130 billion structured relationships, 177 million people tracked, 88 million companies tracked and 31 billion interactions, helping firms uncover opportunities sooner, move with greater conviction and scale institutional knowledge over time.

Learn more: affinity.co

Skills Required

  • Proficiency with data pipeline development, SQL, and cloud data warehousing (Snowflake, BigQuery, Redshift), including ingesting and transforming Salesforce data via APIs or native connectors.
  • Strong dbt experience: modeling, testing, managing projects in a version-controlled, CI/CD workflow.
  • Experience with Git/GitHub and CI/CD deployment pipelines.
  • Write and maintain dbt tests (schema, data, unit) and enforce them in CI.
  • Proficiency with AI-assisted development and analytics tools (e.g., Cursor, Claude/LLMs) and interest in AI-native data workflows.
  • Familiarity with integrating data warehouses into AI/LLM tooling (e.g., MCP, semantic layers for AI consumption).
  • Experience designing and managing Business Data Models (BDM) incorporating Salesforce objects (Accounts, Opportunities, Campaigns).
  • Hands-on Salesforce data management experience, including SOQL, schema understanding, and troubleshooting sync issues.
  • Experience establishing data quality controls, monitoring/alerting for pipeline performance, and performing root cause analysis.
  • Strong communication and collaboration skills with Sales, Marketing, and RevOps stakeholders.
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The Company
HQ: San Francisco, California
299 Employees
Year Founded: 2014

What We Do

Affinity’s patented technology structures and analyzes millions of data points across emails, calendars, and third-party sources to offer users the tools they need to automatically manage their most valuable relationships, prioritize important connections, and discover untapped opportunities. Affinity uses artificial intelligence to analyze relationship strength and illuminate the best paths to warm introductions. The platform also offers a holistic view of users’ networks in a centralized, automatically updated database without any manual upkeep. Founded in 2014, Affinity is headquartered in San Francisco, California. Affinity has raised $120M to date and is backed by leading investors including Menlo Ventures, Advance Venture Partners, 8VC and MassMutual Ventures. It has over 2,700 customers in 70 countries, including venture capital firms such as Bain Capital Ventures and Kleiner Perkins, private equity firms such as SoftBank Group, investment bankers such as Woodside Capital Partners, financial services firms such as Fidelity Investments, real estate companies such as Tishman Speyer, insurers such as American Family Insurance and enterprises such as Nike, Qualcomm and Twilio. Affinity has been named in Fortune Magazine's Best Workplaces, Inc. Magazine's Best Workplaces and editor's number one pick, the Data Breakthrough Award, BIG Innovation Award and others

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