Data Platform Engineer

About EatClub

At EatClub, we believe restaurants and bars are the beating heart of every city’s culture. Whether it's discovering a hidden gem, grabbing a late-night takeaway, or meeting friends for a drink, our mission is simple: help the hospitality industry thrive through smart, powerful tech.

Our platform helps over 4 million customers discover top restaurants and access real-time deals that save them up to 50% off the bill. We empower more than 8,000 venues to fill empty tables, increase foot traffic, and maximise revenue.

#1 app in Food & Drink and awarded Australia's Fastest Growing Tech Company by the AFR in 2025. Now is an exciting time to join our team. Initially co-founded by Marco Pierre White and leaders in the food tech scene, we're now a 200+ person scaleup that's growing fast and making waves in the industry.

Why You'll Love Working With Us

- Operate in an AI-first culture. Claude Code via Anthropic Enterprise, agentic and async workflows expected, humans on final review. This isn't a pilot - it's how the team works every day.
- Own the platform, not a ticket queue. Ingestion, orchestration, governance, cost and reliability across a Databricks lakehouse that every team in the business depends on.
- Work on a genuine industry gamechanger - build the data foundations that give the business a clear, trusted picture of itself and power better decisions at every level.
- Join a small, high-leverage team at the point where the platform is being built properly for the first time. The decisions you make now will still be load-bearing in three years.
- Ship in days, not quarters. Real pipelines, real dashboards, real feedback every week.
- Staff discounts and dining vouchers to enjoy through EatClub

We are looking for a Data Platform Engineer - someone who takes as much pride in a pipeline that never silently fails as in the analytics it powers.

A Day-in-a-Life of our Data Platform Engineer

You will spend your days on the systems underneath the analytics - the ingestion pipelines that bring data in, the orchestration that keeps it moving, the governance that keeps it safe, and the tooling that lets everyone else move fast without breaking things. When a pipeline fails, you're the person who knows why. When the compute bill moves, you can explain it line by line.

You'll work alongside the analytics and data science side of the team, whose models and dashboards run on what you build, and you'll leverage AI tooling to expedite development, testing, migration and review.

There's ambiguity. There's speed. There's ownership.

On any given week, you will:

- Build and operate ingestion into the bronze layer - new source integrations, CDC feeds and third-party APIs - handling schema evolution, backfills and replay properly the first time
- Own orchestration workflows: scheduling, dependencies, retries, alerting, and real SLAs on the datasets the business reads every morning
- Harden our CI/CD - trunk-based development, PR checks, tests that gate deploys, and clean promotion across environments
- Govern the platform: grants, lineage, tagging, row and column-level security, and safe external data sharing with partners
- Own cost and performance - right-size warehouses and clusters, tune partitioning, clustering and incremental strategies, and keep the compute footprint explainable
- Build data quality and observability into the platform: freshness, volume and schema checks, alerting on breaks, and a short path from "this dashboard looks wrong" to root cause
- Make the platform self-serve, so analysts and data scientists can ship without you being directly in the loop

You have

- Solid experience writing and optimising SQL for commercial-scale products, plus strong Python
- Hands-on experience building and operating production data pipelines on a cloud data platform
- Experience with orchestration and scheduling (Databricks Workflows, Airflow, Dagster or similar), including what you actually do when a job fails overnight
- Experience working with internal APIs and third-party tools to ingest data efficiently while maintaining strict data integrity
- A strong grasp of software engineering best practices (Git, CI/CD, trunk-based development, tests)
- Familiarity with an "AI-first" working style: Claude Code, agentic workflows, AI in your daily loop

It would be extra awesome if you also had

- Experience using Databricks and dbt Core
- Familiarity working with AWS
- Cost and performance tuning on Spark or Databricks — partitioning, liquid clustering, warehouse sizing
- Streaming or CDC experience (Structured Streaming, Debezium, Delta Live Tables)
- A track record of implementing data quality, security, and documentation best practices to keep data a trusted "source of truth"
- Contributed to experiments with AI and LLMs to assess how they can be practically applied to solve business problems

Maybe this role is not for you if

- You are not comfortable with a fast paced environment where priorities can shift weekly
- You want to spend most of your time on business-facing analysis and dashboards rather than the systems underneath them
- You're uncomfortable owning ambiguous problems end to end
- You'd rather follow a fully-specified spec than figure out the right design yourself

If you're curious about what we're building, you're welcome to explore EatClub ahead of your interview. First-time users who choose to give it a try can use the code "ECAPPLY5" for an optional $5 voucher to test the experience. This is entirely voluntary and has no impact on your application or interview process.

One last note: even if you feel you don't meet every criterion above, we encourage you to apply. Past work experience is not the only indicator of future success, and we are on the lookout for hungry talent who want to grow with us.