BI Analyst
About the Role
This position involves designing, developing, and maintaining robust data models to support analytical and product data needs across the organization.
A key aspect of this role is building visually appealing, high-performing, and impactful reporting/dashboard products using tools like Tableau/Sigma across large data sets.
Collaboration with data engineers, data scientists, and business stakeholders is crucial in understanding data requirements and translating them into scalable data solutions.
* Data Modeling and ETL/ELT Processes: Implement and optimize ETL/ELT processes to ensure data quality, reliability, and performance.
* KPIs and Reporting: Own and define business KPIs, their measurement plans, data requirements, and reporting.
* Reporting Requirements: Build processes to ensure correct, timely, and reliable reporting.
* Automation: Address ad-hoc reporting requirements and find pathways for automation.
* Design Patterns: Build and enforce common design patterns to increase report reusability, readability, and standardization.
Requirements
* IT Experience: 7+ years of IT experience.
* Business Intelligence Experience: 3+ years of experience working in business intelligence, data analytics, Data engineering, or a similar role.
* SQL Skills: Strong SQL skills and experience with data modeling techniques (e.g., dimensional modeling, 3 Nf, data vault).
* Programming Language Proficiency: Proficiency in a programming language such as Python or Scala.
* Reporting and Dashboarding Tools: Experience building reporting and dashboarding solutions using Tableau, Sigma, Data Lake/Snowflake, or similar ecosystem.
* Database Fundamentals: Expert in database fundamentals, SQL, and performance tuning.
* Communication Skills: Excellent communication skills and experience working with technical and non-technical teams.
Nice to Have
* Real-Time Data Processing: Experience with real-time data processing and streaming technologies.
* Modern Data Warehousing Platforms: Experience with modern data warehousing platforms (e.g., Snowflake, DataBricks, Redshift) and knowledge of data visualization tools (e.g., Looker, Tableau).
* Machine Learning Concepts: Familiarity with machine learning concepts and their data requirements.