Key Facts

Remote From:

Full time

Senior (5-10 years)

English

Hard Skills

Databricks Databricks Python (Programming Language) SQL (Programming Language) Tech Genie Application Analytics Dimensional Modeling Code Analysis Warehouse Management Data Validation +26 more

Other Skills

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Communication
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Teamwork
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Problem Solving

Roles & Responsibilities

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

Requirements:

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

Job description

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.