Data Engineer
Cummins Inc. (company site, opens in a new tab)2–4 yrsPuneOn-siteDirect career pageEst. 8–14 LPA
Posted on 7 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and maintain reliable, scalable ETL/ELT data pipelines and data storage solutions using Azure Databricks, PySpark, Python/Scala, and SQL.
- Design, implement, and optimize Data Lake and Lakehouse architectures on Azure services including ADLS, Event Hubs, and Azure Functions.
- Ensure data quality, integrity, governance, and support continuous improvement within Agile environments applying DevOps and Scrum/Kanban practices.
Minimum Requirements
- Bachelor's degree or equivalent in Computer Science, IT, Engineering, Data Science, or related technical field, or equivalent experience.
- 2–4 years of relevant Data Engineering experience preferred; early-career candidates with relevant academic/technical experience may be considered.
- Strong programming skills in Python/PySpark or Scala, plus SQL proficiency; hands-on experience with Azure Databricks and Azure data services (ADLS, Event Hub, Azure Functions).
- Work Experience Required: 2–4 years of relevant Data Engineering experience preferred
Ideal Candidate Profile
- Experienced in designing and operating large-scale cloud-based data pipelines and storage (Data Lake/Lakehouse) on Azure platforms.
- Proficient in Agile methodologies (Scrum, Kanban) and DevOps for continuous delivery and improvement of data solutions.
- Skilled in implementing data quality, governance, and troubleshooting mechanisms to ensure reliable and maintainable data infrastructure.