Trading since 2017, Gravity Team is one of the leading crypto market makers and liquidity providers, with cumulative trading volumes to date in excess of $400 billion.

We provide 24/7 liquidity across 1,400+ crypto-asset pairs on 30+ exchanges in 15+ countries, representing roughly 1% of global spot trading volume.

We’re looking for a Data Analytics Engineer to help build and scale our next-generation analytics platform in Databricks, powering trusted data products, real-time insights, self-service analytics, and the future of AI-driven decision-making.

What You’ll Do:

• Databricks ingestion and warehouse execution

• Gold models, marts, and semantic layer delivery

• Genie and AI-readiness of the data layer

• Data quality, monitoring, and validation

• Stakeholder enablement and warehouse adoption

• Financial and business reporting support

Team collaboration and ways of working

• Work closely with the BI Lead to turn roadmap items into concrete technical deliverables.

• Provide effort estimates, implementation tradeoffs, and delivery risks.

• Participate in code review, documentation, and shared standards for SQL, notebooks, jobs, and data assets.

• Help strengthen self-service analytics by creating reusable assets and reducing manual workflows.

Qualifications:

Strong fit

• Strong SQL skills and solid Python skills.

• Hands-on experience with Databricks, Spark, Delta Lake, or a similar modern cloud data platform.

• Experience building and maintaining ELT/ETL pipelines, especially with incremental or CDC-based patterns.

• Experience with dimensional modeling, marts, semantic layers, and warehouse-first business logic.

• Experience supporting self-service analytics or BI platforms used by multiple teams.

• Ability to work directly with stakeholders and translate messy business requirements into clean data products.

• Strong debugging, validation, and documentation habits.

Good to have

• Experience with Power BI, Grafana, dbt, Airflow, Kafka, or similar tooling.

• Familiarity with Unity Catalog, fine-grained access patterns, or governed data products.

• Exposure to natural-language BI, semantic metadata, or preparing datasets for AI-facing analytics tools.

• Experience in financial, trading, or crypto-adjacent environments.

• Familiarity with GitLab, Jira, notebooks, and collaborative analytics development workflows.