Senior Data Engineer

🔥 1 hour ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Cummins Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1919

⚡ Energy

🚗 Transport

🔧 Hardware

💰 $75M Grant on 2024-07

Energy • Transport • Hardware

Cummins Inc. is a global power technology leader that designs, manufactures, and distributes a variety of engines and power systems solutions. They offer products that range from diesel and natural gas engines to hybrid and electric power systems, as well as components like turbochargers, fuel systems, and emissions solutions. With a strong emphasis on innovation, Cummins aims to reduce emissions and improve fuel efficiency. The company is dedicated to helping industries navigate the transition to cleaner energy through integrated power solutions suitable for diverse applications such as on-highway, marine, mining, and construction. Additionally, Cummins provides services including remote monitoring, diagnostics, and aftermarket support, reinforcing its commitment to sustainability and customer service excellence.

📋 Description

• Enable reliable data flow at scale by designing and automating deployments for distributed systems that ingest and transform diverse data sources, ensuring consistent and seamless data availability across the organization. • Improve data trust and decision-making by building robust monitoring frameworks that quickly detect and resolve data quality and integrity issues before they impact analytics. • Strengthen data governance and compliance by implementing clear standards for metadata, access control, and data retention, making data easier to discover, secure, and use responsibly. • Accelerate analytics delivery by designing scalable, efficient data pipelines with built-in monitoring and alerting, reducing downtime and improving responsiveness to business needs. • Enhance system performance and efficiency by creating optimized physical data models, indexing strategies, and table relationships that reduce query times and resource usage. • Drive innovation through modern data architecture by leveraging cloud and distributed platforms (e.g., Data Lakes, NoSQL, Hadoop ecosystems) to support high-volume, high-velocity data processing. • Increase productivity through automation by eliminating repetitive manual tasks in data preparation and integration, reducing errors and freeing up teams for higher-value work. • Elevate team capability and delivery speed by mentoring teammates and applying Agile/DevOps practices, ensuring continuous improvement and successful execution of critical analytics initiatives.

🎯 Requirements

• Minimum of 5 years of hands-on experience in data engineering with expertise in Azure Databricks and programming in Scala or Python. • Proven experience in building and maintaining structured streaming pipelines using Spark. • Strong knowledge of big data technologies, including Delta Lake, Apache Spark, Structured Streaming, and SQL. • Experience with Git for version control and CI/CD pipeline management.