We are looking for a proactive and analytical Business Intelligence (BI) Engineer with 3 years of hands-on experience in designing and delivering BI solutions from the ground up. The ideal candidate should have independently delivered multiple BI projects, with a strong foundation in Power BI, Looker, data modeling, analytics, and building custom visualizations using marketplace charts. You will be responsible for transforming complex data into clear, actionable insights that directly support business decisions.
Key Responsibilities:
- Build and deploy end-to-end BI dashboards and reports using Power BI and Looker.
- Design and implement custom visualizations, including those from Power BI/Looker marketplace charts, tailored to business needs.
- Gather requirements from business stakeholders and translate them into effective data models and visualizations.
- Develop and maintain data models, measures, and KPIs for reporting and analysis.
- Perform data validation and troubleshooting to ensure accuracy and consistency.
- Optimize report performance and maintain best practices in BI development.
- Collaborate with data engineers or backend teams to ensure reliable and efficient data sources.
- Present analytical findings to non-technical stakeholders in a clear and actionable manner.
Qualifications & Skills:
Must-Have Skills & Experience:
- Atleast 3 years of experience as a BI Engineer or in a similar data analytics role.
- Hands-on experience building and delivering BI projects from scratch using: Power BI (data modeling, DAX, dashboarding), Looker (dashboard creation, LookML preferred)
- Strong SQL skills for querying and transforming data.
- Proven ability to create data models (star/snowflake schemas) and relationships.
- Experience with custom visualizations, including use of marketplace charts in BI tools.
- Strong analytical skills with the ability to interpret data and drive insights.
- Ability to manage and deliver multiple BI projects independently.
- Experience working directly with business users/stakeholders.
Nice-to-Have:
Experience with cloud data warehouses (e.g., BigQuery, Snowflake, Redshift, etc.).
Familiarity with ETL/ELT processes and tools.
Basic knowledge of scripting or programming languages (e.g., Python for data analysis).
Exposure to data governance and access control best practices.
