Data Warehouse Engineer
WFA Digital Insight
Thrill Labs is building a crypto‑gaming platform that hinges on real‑time insight into player behavior, making the data layer a core competitive advantage. The Data Warehouse Engineer sits at the crossroads of database administration, analytics modeling, and cloud infrastructure, meaning every query and dashboard directly informs product decisions. Unlike a generic data‑engineering gig, this role demands hands‑on ClickHouse tuning, Looker dashboard stewardship, and end‑to‑end pipeline reliability across Kafka and Kubernetes. Candidates who can balance performance optimisation with rigorous data‑quality checks will thrive in the fast‑moving environment Thrill Labs promises. Expect deep ownership of the entire analytics stack, from schema design to monitoring, and a chance to shape how millions of gamers experience the product.
Job Description
About the company
At Thrill Labs, we're not just building a gaming company; we're creating a global sensation. We are the innovative force behind Thrill.com, a groundbreaking crypto gaming venture set to launch soon! Our mission? To build the world’s most epic gaming brand and craft magical experiences for millions of users. Backed by a world-class team, we’re here to redefine the future of gaming.
About the role
We're looking for a hands-on Data Warehouse Engineer to evolve our data. You'll sit at the intersection of database administration, data modeling, keeping our ClickHouse stack performant, our Looker dashboards reliable, and our infrastructure trustworthy.
We're already operating at scale, and the data layer is critical to how we understand our product and our players. If you enjoy deep technical ownership, thrive in fast-moving environments, and care about data quality as much as query performance, we'd love to hear from you.
What You'll Be Doing:
Tune ClickHouse queries for performance and efficiency.
Administer ClickHouse settings, tables, and data structures (act as ClickHouse DBA).
Create and maintain data models and dashboards in Looker.
Implement and monitor data quality checks and validations.
Perform infrastructure work on Kafka, Zookeeper, ClickHouse, and the Kubernetes stack.
What You'll Need:
Hands-on experience tuning queries in relational databases.
Proven database administration experience.
Strong SQL, including window functions and analytical queries.
Working knowledge of Kafka: topics, partitions, offsets, and delivery guarantees.
Familiarity with Linux CLI and shell scripting for troubleshooting and automation.
Experience with Docker and containerized environments.
Understanding of data modeling concepts and data lifecycle management.
Proficiency with Git and version control workflows.
Experience implementing backup/restore strategies for large datasets.
Good command of English (at least B2 equivalent).
Bonus Points for (but could be developed on the job):
ClickHouse administration and advanced query tuning.
Looker administration and LookML modeling.
Experience with data quality frameworks and cross-checks.
Administration of Kafka, Kafka Connect, and Zookeeper clusters.
Knowledge of OLAP/DWH concepts (staging, marts, star/snowflake schemas, Kimball/layering).
Monitoring setup experience (Grafana, Prometheus, or similar).
Experience with infrastructure migrations and IaC automation.
End-to-end understanding of data pipelines and analytics modeling.
Why Join Us?
Join Thrill Labs, where your innovation fuels the evolution of gaming. This isn’t just another role; it’s your chance to impact a worldwide phenomenon. If you’re driven to redefine limits and craft a legendary brand, you belong here.
How to Stand Out
- Highlight any ClickHouse or Looker projects in your resume; concrete examples of query optimisation will stand out.
- Prepare a short walkthrough of a data‑quality pipeline you built, focusing on automation and monitoring.
- Bring a portfolio of Git repositories or Terraform modules that demonstrate your IaC experience.
- Expect scenario‑based interview questions about Kafka partitioning and offset handling; be ready to discuss trade‑offs.
- Emphasise remote‑work discipline: mention your home‑office setup, communication tools, and time‑zone overlap strategy.
- If salary isn’t disclosed, research typical ranges for EU‑based Data Warehouse Engineers and be prepared to negotiate based on total compensation.
- Watch for red flags such as unclear on‑call expectations or lack of defined data‑ownership responsibilities.
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