CASY-MSCCN Jobs

As a Data Engineer you will be responsible for designing, implementing, and managing our data architecture, pipelines, and business systems. You will join a Center of Excellence and collaborate closely with data scientists, analysts, leaders, and other stakeholders to ensure data availability, quality, and reliability. Your work will be instrumental in driving data-driven decision-making across the organization.

Key Responsibilities:

1. Data Pipeline Development: Develop, maintain, and optimize robust ETL (Extract, Transform, Load) processes and data pipelines to ensure efficient data flow from various sources into our data warehouse.

2. Data Architecture: Design and implement data architectures that support the storage, retrieval, and analysis of large datasets, while ensuring data security and compliance.

3. Data Integration: Integrate data from diverse sources, including databases, APIs, streaming data, and more, to create a unified and accessible data ecosystem.

4. Performance Optimization: Continuously improve the performance and scalability of data systems, including query optimization and infrastructure enhancements.

5. Data Quality: Implement data quality checks and data cleansing processes to maintain high-quality gold standard data in the data warehouse.

6. Monitoring and Maintenance: Proactively monitor data pipelines and systems, troubleshoot and resolve issues, and ensure data availability and reliability.

7. Documentation: Maintain thorough documentation of data infrastructure, processes, and best practices for knowledge sharing.

8. Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, embedded and software engineers, to understand data requirements and provide data solutions.

9. Data Governance: Implement data governance policies and standards to ensure data security, privacy, and compliance with regulatory requirements and audits in the strict Life Sciences field.

10. Technology Evaluation: Stay up-to-date with the latest data engineering technologies and evaluate their suitability for our infrastructure.

Qualifications:

• Bachelor's with 7+ years of experience or Master's degree with 5+ years of experience in Computer Science, Information Technology, Engineering or a related field.

• Proven experience as a Data Engineer in a complex data environment.

• Strong proficiency in data warehousing and ETL tools (e.g., Informatica, SQL, Apache Spark, Hadoop, etc.).

• Proficiency in programming languages such as Python, Java, or Scala.

• Expertise in database management systems (e.g., SQL, NoSQL, columnar databases).

• Experience with cloud platforms (e.g., AWS, Azure, GCP) and data technologies (e.g., BigQuery, Redshift, Snowflake).

• Excellent problem-solving and analytical skills.

• Strong communication and teamwork skills.

• Knowledge of data governance, security, and compliance best practices.

Preferred Qualifications:

• Data engineering certifications.

• Experience with real-time data processing and streaming platforms (e.g., Apache Kafka).

• Familiarity with data orchestration and workflow management tools.

• Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

• Experience with Operations and MES systems is a strong plus

At Danaher we bring together science, technology and operational capabilities to accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. Our global teams are pioneering what’s next across Life Sciences, Diagnostics, Biotechnology and beyond. For more information, visit www.danaher.com.

At Danaher, we value diversity and the existence of similarities and differences, both visible and not, found in our workforce, workplace and throughout the markets we serve. Our associates, customers and shareholders contribute unique and different perspectives as a result of these diverse attributes.