Node.js + PostgreSQL Developer — Analytics/Attribution SaaS (Full Stack Developer)

We're building an analytics and attribution product — tracking where customers actually come from and what drives revenue, across first-touch, last-touch, and multi-touch models. Looking for someone who has real experience with ClickHouse and attribution/analytics data specifically, not just general backend work. Stack: Node.js, Express, PostgreSQL, ClickHouse (via Tinybird), React, Railway, Stripe. What the work involves: - Writing and reviewing ClickHouse queries — aggregations, uniqExact/uniq for visitor counts, ASOF joins for touchpoint matching, window functions for attribution models - Auditing and fixing attribution logic — first-touch, last-touch, linear, time-decay, multi-touch models, and making sure a conversion is credited to the right source, not a fallback or a default - Reconciling numbers across ClickHouse and Postgres, and across different dashboard pages, when they disagree - Building integrations (payment providers, webhooks, GSC-style third-party APIs) and making sure the data they bring in is attributed correctly, not just recorded - QA on data correctness specifically — not "does the page load" QA, but"does this number actually mean what it claims to mean" QA - Implementing Figma designs in React for the dashboard What matters most to us: - Real ClickHouse experience — you understand why a row-limited query and a proper aggregate query can give wildly different totals, and why uniqExact doesn't sum across GROUP BY buckets the way count does - Understands attribution modeling well enough to know when "no clear source" should show as unknown, not silently default to "Direct" or another source - Comfortable with NULL handling in ClickHouse and Postgres — knows that functions like toFloat64OrZero don't always coerce NULL to zero the way people assume, and that this quietly corrupts revenue totals - Knows that a database call returning "no error" doesn't always mean the write succeeded, and writes code that checks - Can work independently — this isn't a fully-specced ticket queue, part of the job is noticing problems before they're pointed out Nice to have: - Experience with Tinybird specifically - Experience with marketing attribution, UTM tracking, or multi-touch revenue modeling - Comfortable using AI coding tools (we use Claude Code) — can explain their reasoning, not just submit code To apply, answer both briefly: 1. A backend endpoint returns HTTP 200 and marks the response as successful, but the data it just wrote to the database never actually landed. What are 2-3 ways this can happen, and how would you catch it before a user does? 2. A dashboard shows "45 visitors" on one page and "1,835 visitors" on another page for the same site and the same date range. What are 2-3 things you'd check first to figure out why? Keywords: ClickHouse, Tinybird, Node.js, PostgreSQL, Attribution Modeling, Marketing Attribution, Multi-Touch Attribution, SQL, Aggregation, Data Pipeline, Analytics Engineering, SaaS, Backend Development, REST API, Webhook Integration