Business Intelligence (BI) Engineer

Role overview

Business Intelligence (BI) Engineer at Beckman Coulter Diagnostics

The primary objective of this role is to build analytics strategies that align with business priorities and drive measurable business outcomes.

Responsibilities

• Design, develop, and maintain reporting and analytics solutions using Microsoft Fabric, Power BI, and modern cloud analytics platforms.
• Collaborate with data engineering teams to define semantic models and analytics data products.

Preferred qualifications and skills

• It would be a plus if you also possess previous experience in.

Employment details

• Location: Bangalore [Karnātaka] [India], Pune [Mahārāshtra] [India]

Additional role details

• The BI Engineer is responsible for designing and improving Danaher’s data management & analytics function.
• Build and optimize semantic models, measures, and KPIs that support business and operational decision making.
• Partner with business stakeholders to translate complex business requirements into intuitive dashboards, reports, and actionable insights.
• Explore innovative approaches for analytics applications using Streamlit, Fabric, and emerging AI enabled reporting capabilities.
• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or related field (or equivalent experience). 5+ years of experience developing enterprise reporting, business intelligence, or analytics solutions.
• Advanced experience with Microsoft Fabric, Power BI including semantic models, DAX, Power Query, Row-Level Security (RLS), and Fabric analytics capabilities.
• Strong understanding of dimensional modeling, star schemas, and analytics data modeling principles.
• Experience gathering requirements and partnering directly with business stakeholders to define KPIs and reporting solutions.
• Proficiency in SQL and experience analyzing data from modern cloud based data platforms.
• Snowflake and modern cloud data warehouse platforms.
• Data engineering technologies such as Python, PySpark, Fabric Notebooks, and ETL/ELT pipelines.
• Learn about the Danaher Business System which makes everything possible.