Senior Analytics Engineer - Databricks, Semantic Layer & AI Readiness

About Us

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.

The Role

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.

Responsibilities

• 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

Requirements

• 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

Nice 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