Data Engineer

Data Engineer

• 25001556

Position Qualification Summary:

Key Responsibilities:

• Design and Develop Data Pipelines: Architect, build, and maintain scalable data pipelines leveraging Apache Spark and Microsoft Fabric to process large volumes of structured and unstructured data from diverse sources.
• Data Integration: Integrate data from internal and external sources, ensuring accuracy, consistency, and reliability throughout the data lifecycle.
• Performance Optimization: Monitor and optimize ETL/ELT processes for performance, scalability, and cost-efficiency, proactively identifying bottlenecks and implementing improvements.
• Data Quality and Governance: Implement best practices for data quality, data cataloging, and lineage, and support governance policies to ensure compliance and high standards.
• Collaboration: Work closely with data scientists, analysts, business stakeholders, and cross-functional IT teams to gather requirements, deliver insights, and support analytical models.
• Documentation: Prepare and maintain detailed documentation for data workflows, pipeline architectures, data schemas, and processes.
• Continuous Improvement: Stay current with emerging trends and technologies in data engineering, suggesting and implementing innovative solutions to enhance the data platform.
• Troubleshooting: Diagnose, debug, and resolve data pipeline and infrastructure issues to ensure robustness and reliability of the data ecosystem.
• Security: Adhere to and enforce data security and privacy guidelines, ensuring sensitive data is handled appropriately.

Qualifications:

Basic:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 2 years of professional experience in data engineering, data architecture, or a related domain.
• Proven experience working with Apache Spark for large-scale data processing (batch and streaming).
• Hands-on expertise with Microsoft Fabric (formerly Power BI Dataflows, Data Factory within Fabric, or similar cloud-based data integration platforms).
• Strong proficiency in SQL, Python, and/or Scala for data manipulation and ETL development.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud, with a preference for Azure.
• Solid understanding of distributed systems, data warehousing, and data modeling concepts.
• Demonstrated ability to design, implement, and optimize ETL/ELT workflows.
• Knowledge of data governance principles and data quality management.
• Excellent problem-solving skills and meticulous attention to detail.
• Strong communication and teamwork abilities, with a collaborative approach to project delivery.

Preferred:

• Professional certifications in Apache Spark, Azure Data Engineering, or Microsoft Fabric/Power Platform.
• Experience with real-time data processing and streaming frameworks (e.g., Kafka, Azure Event Hubs).
• Knowledge of DevOps practices for data pipelines, including CI/CD, automated testing, and infrastructure as code.
• Experience with data visualization and reporting tools (e.g., Power BI, Tableau).

About Linde:

Linde is a leading global industrial gases and engineering company with 2024 sales of $33 billion. We live our mission of making our world more productive every day by providing high-quality solutions, technologies and services which are making our customers more successful and helping to sustain and protect our planet.

Culture:

At Linde, we strive to create a work environment that treats all employees with respect, supports new thoughts and ideas, encourages growth and development, celebrates our differences, and embraces inclusion. Linde is committed to remaining an employer of choice for the diverse, ever-increasing pool of global talent.

For more information about the company and its products and services, please visit www.linde.com.

Pay commensurate with experience. Open to salary range $88,875 - $130,350.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, pregnancy, sexual orientation, gender identity or expression, or any other reason prohibited by applicable law.

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