3 days ago
Pune, IndiaSenior
Responsibilities
- Develop and maintain enterprise data products, pipelines, transformations, and curated datasets for reporting, analytics, automation, machine learning, and GenAI use cases.
- Build scalable ETL/ELT pipelines that ingest and transform relational, event-based, and unstructured data sources.
- Implement deployment automation, monitoring, alerting, troubleshooting, and data quality and integrity controls for distributed data systems.
- Design physical data models and data storage architectures using distributed and cloud-based platforms.
- Apply data governance practices covering metadata, lineage, access, retention, and discoverability of data assets.
- Create reusable, governed, and self-service data products using Data-as-a-Product principles.
- Translate business and product requirements into scalable, performant, maintainable, and reusable technical solutions.
- Collaborate with Product Managers, Data Engineers, Data Scientists, Solution Engineers, analysts, and business stakeholders.
- Participate in data pipeline testing, solution validation, documentation, and continuous improvement.
Requirements
- Relevant college or university degree in a technical discipline, or equivalent relevant experience.
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or equivalent practical experience.
- Experience developing and supporting data integration, ETL/ELT processes, data pipelines, and data transformations with modern cloud-based data platforms.
- Working knowledge of data modeling, SQL, data quality practices, metadata management, and data governance principles.
- Ability to develop and support scalable enterprise data products and translate stakeholder requirements into technical solutions.
- Experience working in Agile, cross-functional teams with product, engineering, analytics, and business stakeholders.
- Preferred exposure to big data open-source technologies, Spark, Scala or Java, MapReduce, Hive, HBase, Kafka, clustered cloud computing, large-file movement, analytical solutions, and IoT.
- Preferred experience with Data-as-a-Product operating models, data catalogs, lineage, data quality frameworks, certified data products, AI/ML initiatives, or GenAI-ready datasets and semantic models.
- Relevant experience from temporary student employment, internships, co-ops, extracurricular team activities, or equivalent coursework is preferred.
- The position may require licensing for compliance with export controls or sanctions regulations.
Tech Stack
Amazon DynamoDBApache CassandraApache HadoopApache HBaseApache HiveApache KafkaApache SparkJavaMongoDBScalaSQL
Categories
Data Engineering
About Cummins
Cummins Inc. designs and manufactures diesel, natural gas, and electrified powertrains, generators, and related components (turbochargers, filtration, emission systems) for commercial vehicles, industrial equipment, marine, rail, and power markets. It sells to OEMs and fleet operators and provides parts and service through a global distribution network. Founded in 1919 and headquartered in Columbus, Indiana, Cummins is a public company listed on the NYSE (CMI).