Strong Middle Senior/Senior BI Analyst
Remote
Colombia
Ukraine
Our customer is a world leader in entertainment.
You will build dimensional analytics infrastructure (dbt + Snowflake) for a high-volume live events ticketing & hospitality business. Transform existing Snowflake source data into production-ready BI models for commercial strategy, pricing, and revenue optimization.
Work schedule till 20:00 (UA) or US Central timezone overlap availability (CO).
Requirements:
- 5+ years building dimensional data models in production (facts and dimensions)
- Expert SQL + dbt with deep understanding of materialization strategies (views, tables, incremental)
- Snowflake production experience
- Git workflows: pull requests, code review, peer review collaboration
- Code quality adherence: linting, pre-commit hooks, following team conventions
- Strong data validation and quality assurance skills
- Experience debugging and correcting transformation logic
- Can deliver independently with minimal supervision while collaborating effectively with Analytics/Data Platform teams
- Portfolio required: GitHub or similar showing dimensional modeling/dbt work
- At least Upper Intermediate English level
Preferred:
• E-commerce/ticketing/transactional business experience
• Experience with cross-system data reconciliation
• BI platform integration knowledge (Tableau, Omni Analytics, Looker)
Responsibilities:
- Expected Effort Distribution: 20% setup/design > 30% initial model building > 40% validation/iteration > 10% documentation/handoff
- Scope Boundaries: All source data exists in Snowflake Landing layer (Bronze). You will build the Analytics layer (Silver) dimensional models – facts and dimensions. Analysts will create their own Marts (Gold layer) using Omni Analytics for self-service BI, so your dimensional models – especially dimensions – must be production-ready, well-documented, and high quality for direct downstream consumption. You will not build data ingestion pipelines, orchestration workflows, or final BI dashboards.
- Expect significant time on validation work: fixing data quality issues, implementing complex business rules, and iterating based on stakeholder feedback to ensure accuracy.
- Code Review Process: All code pushed to GitHub for peer review and approval by Data Platform team before merging. Must adhere to established linting standards, pre-commit hooks, and data platform conventions.
- Strong collaboration and communication with Data Platform team required throughout implementation.
