Staff Data Engineer – GTM

Staff Data Engineer – GTM Overview

Join a dynamic team at Fin, a leading AI Customer Agent company, as a Staff Data Engineer in our Go-To-Market (GTM) division. This role is pivotal in shaping the foundation of account and contact data that drives our business decisions. You will be responsible for building and managing systems that define account identities, resolve duplicates, and enrich data to enhance our customer support capabilities.

Key Responsibilities

• Take ownership of account identity by building and enhancing the entity-resolution layer that determines when two records represent the same company, including domain and firmographic matching, confidence scoring, and maintaining clean Salesforce data.
• Design and model account hierarchies, linking accounts to their parent organizations, top operating parents, and ultimate corporate parents.
• Develop account sourcing pipelines that convert market definitions into ranked, deduplicated, CRM-ready account lists, utilizing both third-party and internal signals, scoring fit, and integrating accounts into Salesforce with appropriate ownership and metadata.
• Create contact sourcing and enrichment pipelines to identify key individuals at target accounts, ensuring verification and enrichment while adhering to privacy and consent regulations, and delivering this data into the tools used by sales and marketing teams.
• Implement LLM-powered enrichment processes that enhance the existing framework by utilizing web search and crawling tools across various providers to gather unique insights about target companies.
• Ensure data usability by organizing everything into well-structured, thoroughly tested dbt models in Snowflake, orchestrated with Airflow, and syncing data to Salesforce, Marketo, Clay, and other components of the GTM stack.
• Maintain data quality and trust by equipping your pipelines with tests, alerts, and reconciliation processes to identify issues before they affect sales representatives, and serve as the go-to person for any discrepancies in data.
• Collaborate closely with Sales, Marketing, and Operations teams to understand their objectives and propose data solutions that facilitate their goals.

Required Qualifications

• Demonstrated interest in business growth and a strong affinity for go-to-market teams, with a curiosity about sales and marketing processes.
• Proficiency with modern data stack technologies, including dbt, a cloud data warehouse (preferably Snowflake), and a DAG orchestrator (such as Airflow).
• Experience in deploying LLMs in production environments, including prompt design, evaluation, tool/function calling, web search, and crawling, while managing cost and latency.
• Familiarity with entity resolution, identity, or deduplication challenges, including the ability to match complex real-world records and assess precision/recall trade-offs.
• Hands-on experience with integrating SaaS APIs and business systems, particularly Salesforce, including both data retrieval and data writing.
• Excellent communication skills, capable of explaining technical concepts to both technical and non-technical stakeholders.
• A growth mindset with a willingness to learn and adapt to rapidly evolving tools and technologies.

Benefits

• Hybrid working policy requiring employees to be in the office at least three days per week to foster collaboration and culture.
• Comprehensive benefits and programs designed to support health, wellbeing, family needs, time off, and financial future, varying by location.

Degree Requirement: Not Specified

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