Staff Data Engineer, Reporting & Analytics

🕒 February 18

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Danaher Corporation

WebsiteLinkedInAll Job Openings

10,000+ employees

🧬 Biotechnology

🔬 Science

🤝 B2B

Biotechnology • Science • B2B

Danaher Corporation is a leading global life sciences and diagnostics innovator that develops and supplies instruments, technologies, software, and services to accelerate scientific research, biotechnology development, and clinical diagnostics. The company operates through businesses focused on biotechnology tools, diagnostics platforms, and life sciences products, leveraging the Danaher Business System and an acquisition-driven strategy to scale technologies and support customers across academia, pharmaceutical and biotech companies, and clinical laboratories.

📋 Description

• Data Engineer builds and maintains analytics-ready datasets optimized for reporting and dashboards for consumption by all Danaher Opcos. • Enable self-service access through semantic layers, catalogues, and APIs, empowering data scientists, analysts, and business teams to consume data without deep pipeline knowledge. • Partner with stakeholders to translate business questions into clear, accurate metrics. • Ensure data accuracy, freshness, and consistency across reporting surfaces. • Implement testing, documentation, and quality checks for data analytics.

🎯 Requirements

• Minimum 8 years' experience in analytics engineering, reporting, or business intelligence. • Advanced proficiency in PySpark for advanced data processing tasks. • Hands-on experience delivering Fabric/Databricks lakehouse solutions with medallion architecture, leveraging Dataflow Gen2, Fabric Pipelines, and PySpark Notebooks in OneLake/Lakehouse. • Strong knowledge of Power BI architecture, including DirectQuery, Composite Models, Row-Level Security (RLS), Object-Level Security (OLS), Dashboards. • Build and manage complex ETL/ELT workflows that extract, transform, and load data for downstream analytics and reporting. • Strong understanding of CI/CD practices, DevOps. • Hands-on experience with cloud data ecosystems (AWS, Azure) designing high-volume, high-availability data pipelines.

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities