Senior Analytics Engineer - GTM

Salary

$196,000 - $269,500

Location

San Francisco, CA

Posted

Yesterday

Are you passionate about using data and AI to shape the future of Faire's Go-to-Market (GTM) strategy, sales, and operations? If so, we want to talk to you! We're looking for a technical owner in our team to work closely with Revenue Operations, GTM Systems Engineers, Data Scientists, Product Analysts and Software Engineers to support revenue-driving GTM initiatives by designing and building scalable data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve GTM data consumption workflows (e.g., Snowflake, BI tools, Salesforce), and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.

Join us and be part of a team that values data-driven innovation and excellence.

What you'll do

The ideal candidate will possess a perfect blend of data engineering technical expertise and the product sense to be able to translate internal customer needs into practical solutions. They will have strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on GTM data initiatives.

Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
Lead the technical execution in building scalable data models and pipelines for a GTM domain defining the architecture, data requirements, and roadmap (e.g., Contact Scoring, Lead Qualification, Sales Pipeline, Sales Enablement).
Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows.
Optimize processes for operational excellence in project management and system reliability.
Ensure security standards are met within data systems and workflows.
Ensure and promote data quality standards for accurate and reliable insights.
Embrace emerging technologies with enthusiasm.

Minimum qualifications

4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
Production-level development experience in Python.
Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
Experience with Airflow, Docker, DBT or similar analytics workflow tools.
BA/BS degree in Computer Science, Math, Physics, or a related technical field.

Nice to haves

Experience with GTM specific data modeling using a BI tool such as Looker or similar while leveraging conversational analytics. Build and own the GTM semantic layer.
Hands-on experience with GTM-specific data and platform apps, including Reverse ETL (e.g., Hightouch), ELT/Ingestion tools (e.g., Fivetran), iPaaS/Integration platforms (e.g., Workato, N8N, Zapier), and CRM/GTM systems and tool (e.g., Salesforce, Clay).

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