Data Platform Engineer

About the role

ABOUT BLOCK LABS

Block Labs is a premier technology studio operating at the bleeding edge of Web3, Artificial Intelligence, and iGaming. We don't just ship features; we engineer high-scale, production-grade platforms that power the next generation of digital products.

We are a collective of senior engineers, product strategists, and builders who refuse to compromise on architecture. Whether we are designing autonomous multi-agent AI systems, building decentralized financial infrastructure, or architecting high-frequency iGaming platforms, our standard is excellence.

We move fast, but we build for the long term. If you are looking to work alongside a team that values deep technical expertise, thoughtful system design, and product ownership, Block Labs is where you belong.

THE ROLE

Data & Intelligence now sits at the centre of several products we are developing, and we need a platform that is both dependable and capable of supporting more advanced intelligence over time.

This role reflects that shift. We are designing a new data platform that will act as the backbone for everything from real time decisioning to predictive modelling. As a Data Platform Engineer in the Data Team, you will own the end-to-end real-time pipeline, serving data across a unified analytical warehouse and feature-serving layer. You are not building dashboards. You are engineering the commercial nervous system of a multi-tenant platform designed to scale from one operator to 10x with marginal infrastructure cost.

KEY RESPONSIBILITIES:

- Design, build, and maintain scalable data pipelines using AWS Glue (PySpark), or equivalent orchestration and transformation tools.

- Engineer and optimise the ClickHouse warehouse for sub-second query performance across all back-offices.

- Implement data contracts between back-office and the platform. Onboarding a new operator is a config change, not new tables, topics, or feature views.

- Build the feature-serving layer providing pre-computed features to AI agents at millisecond latency.

- Integrate with third-party databases, back-office APIs, and external systems (CRM, affiliates, acquisition platforms).

- Establish monitoring, alerting, and maintenance procedures including pipeline health checks, freshness monitoring, anomaly detection, and data contract SLA enforcement.

- Own CI/CD and infrastructure-as-code for data workloads.

- Collaborate with data scientists, agent engineers, BI developers, and infrastructure teams to translate data requirements into reliable, production-grade pipelines.

ABOUT YOU:

- 3+ years building and operating production data pipelines at scale, with hands-on experience across both streaming and batch paradigms.

- Expertise in Apache Kafka (or Amazon MSK): topic design, consumer group management, offset handling, schema registry operations, and production troubleshooting of lag, rebalancing, and throughput issues.