Lead Data Engineer

Role overview Lead the design and production rollout of a multi-tenant Lakehouse that turns streaming and batch data into reliable analytics for business clients. You’ll own the architecture from Kafka ingestion through ClickHouse data marts, with tenant isolation, access controls, and repeatable onboarding built into the platform.

Responsibilities - Design the Lakehouse and enforce tenant separation across storage, catalogs, models, and serving layers. - Build Kafka ingestion and stream processing for product activity, transactions, betting activity, promotions, and partner feeds. - Develop batch and ELT transformations in dbt, and orchestrate pipelines in Airflow, including workflows for adding tenants. - Create ClickHouse data marts for responsive analytics and BI, and improve query performance and cost as usage grows. - Set up tenant-aware roles, access auditing, data quality checks, monitoring, alerts, and technical documentation. - Work with analytics, BI, and product colleagues to shape raw data into dependable client-facing datasets and guide architecture and tooling decisions.

Requirements - At least six years of data engineering experience, including designing data warehouses or lakes. - Advanced SQL and strong Python skills; practical experience with Kafka and stream processing, Airflow, and ClickHouse. - Experience building multi-tenant or B2B analytics systems, including tenant-aware models, data isolation, and access controls. - Knowledge of Lakehouse SQL engines and data modeling across raw, staging, and mart layers, including dimensional models, slowly changing dimensions, incremental loads, and tenant partitioning. - Understanding of row-level security, role-based access, and access auditing. - Experience with data CI/CD, testing, version control, and documentation, plus the ability to own architecture and delivery independently.

Nice to have - Experience in betting or iGaming, or familiarity with metrics such as GGR, NGR, LTV, RTP, retention, and conversion funnels. - Experience with Elasticsearch, Terraform, Docker, Kubernetes, BI tools, or self-service analytics for external clients. - Background in cloud cost optimization, tenant onboarding, or templated pipelines.

Benefits and work setup - Fully remote work and a competitive salary. - Opportunity to influence product quality directly, with low bureaucracy and collaboration across development and product teams. - Career growth opportunities and technically varied work.