
Posted 8 days ago
Lead Data Engineer
AI Summary
Designs and builds a multi-tenant Data Lakehouse with tenant isolation, Kafka ingestion, dbt/Airflow pipelines and ClickHouse marts for B2B iGaming analytics. Owns architecture and tenant onboarding.
About this role
ZEXTER is a technology company developing its own full-stack platform for the digital entertainment and iGaming ecosystem. We build scalable technology solutions foroperators, creators, and digital businesses, helping them launch, manage, scale and monetize their products more efficiently.
We are looking for a Lead Data Engineer to design a multi-tenant Lakehouse and take it to production: from ingestion via Kafka to data marts in ClickHouse, with data isolation, role-based access, and onboarding of new tenants.
Responsibilities:
Design a multi-tenant Data Lakehouse architecture
Build tenant data isolation across all layers: storage, catalog, data marts, and access.
Build ingestion and stream processing via Kafka: website/app events, transactions, bets, bonuses, and partner data.
Develop batch/ELT pipelines and transformations in dbt with per-tenant logic.
Orchestrate pipelines in Apache Airflow, including onboarding of new tenants.
Design data marts and the serving layer in ClickHouse for fast B2B analytics and BI.
Implement access segregation: tenant-aware roles, and access auditing.
Set up data quality, monitoring, alerting, and tenant-level documentation.
Optimize cost and query performance as the number of tenants grows.
Participate in tool selection and architectural decisions.
Work with analysts, BI, and product teams: turn raw data into clear and reliable datasets for B2B clients.
Account for security, isolation, and, where applicable, iGaming regulatory requirements.
Requirements:
6+ years in Data Engineering.
Advanced SQL and strong Python.
Experience designing data warehouses/data lakes
Experience building multi-tenant analytics platforms or B2B analytics: data isolation, tenant-aware models, access segregation.
Experience with Apache Kafka and stream processing.
Experience with Apache Airflow.
Experience with analytical databases, ClickHouse is a must.
Understanding SQL engines over a Lakehouse.
Data modeling experience: raw/staging/marts layers, dimensional models, SCD, incremental loads, per-tenant partitioning.
Understanding of row-level security, role-based models, and access auditing.
Experience with data CI/CD, data tests, versioning, and documentation.
Ability to work autonomously and take ownership of architecture and results.
Nice to Have:
Experience in iGaming / betting / gambling.
Understanding of GGR, NGR, LTV, RTP, retention, and funnel metrics.
Experience with ElasticSearch.
Experience with Terraform, Docker, Kubernetes.
Experience with BI tools and building self-service analytics for external clients.
Experience optimizing cloud cost under multi-tenant load.
Experience with tenant onboarding and pipeline templating.
What we offer:
Fully remote work.
Competitive salary.
Opportunity to work in a fast-growing international iGaming company.
Strong Development and Product teams.
Minimal bureaucracy and the opportunity to directly influence product quality.
Clear career path with the opportunity to grow.
Interesting challenges and modern tools.
Skills
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