Business Intelligence Analyst, gTech Analytics, Platforms and Tools
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience in Business Intelligence or Data Analytics.
- 2 years of experience in SQL and Data Visualization (e.g., Looker, Tableau, Power BI, Qlik, or similar technologies).
- 2 years of experience with data warehousing and building data pipelines (e.g. extract, transform, load).
- Experience with Python or similar scripting languages.
Preferred qualifications:
- Experience translating ambiguous business needs into clear technical requirements for impactful data products.
- Experience deploying data products, collaborating across teams, and driving user adoption through targeted communication.
- Experience in business or Customer Service, demonstrating a customer-centric approach.
- Experience in developing BRDs/PRDs/Design Docs, code reviews, etc.
- Experience communicating complex technical solutions and analysis to executive stakeholders.
- Experience managing multiple projects concurrently under deadlines in a fast-paced environment.
About the job
As a Business Intelligence (BI) Analyst, you will empower gTech Ads teams to make data-driven decisions by delivering integrated BI solutions that translate complex data into actionable insights. You will leverage internal data systems to design intuitive dashboards, maintain robust data pipelines, and develop tools that automate analyses and insights, ensuring efficient access to metrics and driving impactful business decisions.
Responsibilities
- Design dashboards, reports, and self-service solutions to communicate complex data findings.
- Build and maintain data pipelines, ensuring data integrity and resolving anomalies.
- Work cross-functionally with business stakeholders to gather requirements, prioritize projects, and deliver impactful data products.
- Translate ambiguous business requirements into technical solutions and address Business Intelligence challenges with innovation.
- Demonstrate technical leadership by implementing best practices, sharing knowledge, and mentoring others on data concepts and tools.
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