Staff Data Engineer - GTM
Intercom · Dublin, Ireland; London, England
Skills in this posting
Extracted from the posting text by the instrument — the demand side, read literally.
The posting
Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences.
Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce.
Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams.
Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.
What is the opportunity?
Every go-to-market decision at Intercom, who we target, who owns the account, what we know about them, what we should say next - rests on a foundation of account and contact data. Getting that foundation right is one of the highest-leverage engineering problems in the company: a single account hierarchy fix can re-route territory, pipeline credit and forecast for thousands of accounts at once.
This role owns that foundation. You will build and run the systems that decide what an account is , resolving duplicates, stitching subsidiaries into corporate hierarchies, sourcing new accounts and contacts into our CRM, and enriching them with firmographic, technographic and intent signals.
Increasingly using LLMs and web research rather than off-the-shelf vendors. Your work is used daily by Sales, Marketing, Partnerships, Sales Ops and Finance, and directly shapes how efficiently Intercom grows.
You will sit in the Data group and partner extremely closely with GTM Systems, RevOps and the frontline teams. This is a role for an engineer who wants to be in the business, not adjacent to it. Someone who gets energy from a rep saying "this list is exactly right" and from watching a pipeline they built turn into revenue.
What will I be doing?
Owning account identity. Building and improving the entity-resolution layer that decides when two records are the same company: domain and firmographic matching, confidence scoring, and the merge/dedupe pipelines that keep Salesforce clean at scale.
Modelling account hierarchy. Designing the organisation spine that links accounts to their parent, top operating parent and ultimate corporate parent.
Building account sourcing pipelines. Turning market definitions into ranked, deduplicated, CRM-ready account lists: sourcing from third-party and internal signals, scoring fit, and pushing accounts into Salesforce with the right owner and the right metadata.
Building contact sourcing and enrichment pipelines. Finding the right people at target accounts, verifying and enriching them, respecting privacy and consent requirements, and delivering them into the tools reps and marketers actually work in.
Building LLM-powered enrichment. Extending our enrichment framework — LLM jobs with web search and crawling tools across multiple providers, to answer questions no vendor sells: what support channels does this company run, are they hiring CS or sales roles, do they ship an AI product, how ready are they for Fin.
Making the data usable. Landing everything in well-modelled, well-tested dbt models in Snowflake orchestrated in Airflow, and syncing it out to Salesforce, Marketo, Clay and the rest of the GTM stack.
Owning quality and trust. Instrumenting your pipelines with tests, alerts and reconciliation so problems surface before a rep finds them, and being the person GTM comes to when a number looks wrong.
Partnering on the problem, not the ticket. Sitting with Sales, Marketing and Ops to understand what they are actually trying to do, then proposing the data foundation that unlocks it.
What skills do I need?
A genuine interest in growing the business and a real affinity for GTM teams. You are curious about how sales and marketing work, comfortable in a room full of reps, and motivated by commercial outcomes rather than only technical ones.
Experience with the modern data stack: dbt, a cloud warehouse (we use Snowflake), and a DAG orchestrator (we use Airflow).
Experience building with LLMs in production: prompt design and evaluation, tool/function calling, web search and crawling, cost and latency control.
Experience with entity resolution, identity or deduplication problems — matching messy real-world records, and reasoning about precision/recall trade-offs where a false merge has a real business cost.
Hands-on experience integrating with SaaS APIs and business systems, especially Salesforce: reading from them, writing back to them.
Strong communication: you can explain a hierarchy change to a CRO and a merge heuristic to an engineer, on the same day.
A growth mindset and eagerness to learn — the tooling in this space is changing fast.
Nice to haves
Experience with GTM data vendors and tooling — ZoomInfo, Apollo, Clearbit, Clay, Crossbeam, Marketo, Census/Fivetran, Gong.
Experience with territory design, account scoring, propensity models or ICP definition.
Exposure to privacy and compliance considerations around contact data (GDPR, CCPA, consent management).
Benefits
We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!
Competitive salary and equity in a fast-growing start-up
We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
Regular compensation reviews - we reward great work!
Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.
Pension scheme & match up to 4%
Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
Flexible paid time off policy
Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
MacBooks are our standard, but we also offer Windows for certain roles when needed.
#LI-Hybrid
Policies
Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.
We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications.
We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values .
Excerpt from the original listing. The full, current text lives at the source. Read and apply there →
The PivotHop read
- What a data engineer actually earnsmedian, seniority, by country
- What data engineers do insteadevery measured route out
- Data Architect → Data Engineer48% readiness
- Data Analyst → Data Engineer31% readiness
- All open data engineer rolesthe full board
Where these skills also reach
Adjacent occupations measured from the same postings — readiness is what a data engineer’s profile already covers.
- 27 open data architect roles92% readiness from data engineer
- 238 open data analyst roles60% readiness from data engineer
- 574 open solutions architect roles59% readiness from data engineer
- 32 open database administrator roles58% readiness from data engineer
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