Company Description
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job Description
- 6+ years of experience in Data Analytics, Business Intelligence, Reporting, or BI Development.
- Strong hands-on experience with MicroStrategy (MSTR).
- Experience with MSTR Reports, Dashboards/Dossiers, Metrics, Attributes, Filters, Prompts, Intelligent Cubes, and Datasets.
- Experience with Logi Analytics / Logi Symphony, or strong experience in another BI platform with the ability to learn Logi quickly.
- Strong proficiency in SQL, including joins, aggregations, CTEs, window functions, and query optimization.
- Strong understanding of data analysis, data validation, and reconciliation.
- Experience developing reports, dashboards, and data visualizations.
- Ability to analyze existing BI solutions and understand underlying business and calculation logic.
- Good understanding of relational databases, data warehousing, and dimensional data modeling.
- Experience working with business stakeholders to gather and clarify requirements. Strong problem-solving, analytical, and communication skills
AI Skills (required For All Roles)
- Daily, fluent use of Claude Code and/or GitHub Copilot for implementation, refactoring, test generation, and code review
- Ability to establish team standards for AI-assisted development: effective prompting, trust-vs-verify discipline on generated code, security/IP guardrails, and reviewing AI-authored changes
- Working understanding of LLM fundamentals: context windows, tokens, model selection, and prompt/context engineering
- Experience integrating AI into developer workflows and agentic/automation tooling (MCP servers, AI-driven CI steps, codegen and doc-generation pipelines)
- Able to evaluate AI tooling pragmatically: measuring real productivity and quality impact, not hype