3 days ago
Pune, IndiaStaff+
Responsibilities
- Develop and maintain enterprise data products through data pipelines, transformations, and curated datasets.
- Build and operate scalable ingestion, processing, and storage solutions for relational, event-based, and unstructured data.
- Implement ETL/ELT processes, deployment automation, monitoring, alerting, and data quality controls.
- Develop physical data models and data storage architectures that support scalable, reliable, and reusable data products.
- Manage metadata, lineage, access, retention, governance, and data integrity for internal and external consumers.
- Translate business and product requirements into maintainable, performant, and scalable technical solutions.
- Collaborate with product, engineering, analytics, data science, solution engineering, and business stakeholders.
- Support AI-ready datasets, semantic models, knowledge assets, and data structures for analytics, machine learning, and GenAI applications.
- Participate in testing, validation, troubleshooting, documentation, and continuous improvement of data pipelines and solutions.
Requirements
- College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent 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 data platforms and cloud-based technologies.
- Working knowledge of data modeling, SQL, data quality practices, metadata management, and data governance principles.
- Ability to translate business and product requirements into efficient solutions while considering scalability, performance, maintainability, and reusability.
- 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, Map-Reduce, 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 initiatives.
- This 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).