Senior Data Engineer

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April 22

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Cummins Inc.

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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.

10,000+ employees

Founded 1919

⚡ Energy

🚗 Transport

🔧 Hardware

💰 $75M Grant on 2024-07

📋 Description

• Deploy distributed systems for ingesting and transforming data from various sources (relational, event-based, unstructured). • Implement frameworks to monitor and troubleshoot data quality and integrity issues. • Establish processes for managing metadata, access, and retention for internal and external users. • Build reliable, efficient, scalable, and quality data pipelines with monitoring and alert mechanisms using ETL/ELT tools or scripting languages. • Design and implement physical data models to optimize database performance through efficient indexing and table relationships. • Optimize, test, and troubleshoot data pipelines. • Develop and operate large-scale data storage and processing solutions using distributed and cloud-based platforms (e.g., Data Lakes, Hadoop, Hbase, Cassandra, MongoDB, Accumulo, DynamoDB). • Use modern tools and techniques to automate common, repeatable, and tedious data preparation and integration tasks. • Renovate data management infrastructure to drive automation in data integration and management. • Ensure the success of critical analytics initiatives using agile development technologies such as DevOps, Scrum, Kanban. • Coach and develop less experienced team members.

🎯 Requirements

• ETL/Data Engineering Solution Design and Architecture: Expert level. • SQL and Data Modeling: Expert level (ER Modeling and Dimensional Modeling). • Team Leadership: Ability to lead a team of data engineers. • MSBI (SSIS, SSAS): Experience required. • Databricks (Pyspark) and Python: Experience required. • Additional Skills: Snowflake, Power BI, Neo4j (good to have). • Communication: Good communication skills. • 8+ years of overall experience. • 5+ years of relevant experience in data engineering. • Knowledge of the latest technologies and trends in data engineering. • Familiarity with analyzing complex business systems, industry requirements, and data regulations. • Big Data Platform: Design and development using open source and third-party tools. • Tools: SPARK, Scala/Java, Map-Reduce, Hive, Hbase, Kafka. • Proficiency in SQL query language. • Experience with clustered compute cloud-based implementations. • Experience developing applications requiring large file movement for cloud environments. • Experience in building analytical solutions. • Intermediate experience preferred in IoT Technology. • Intermediate experience preferred in Agile Software Development.