3 days ago
Pune, IndiaMid Level / Senior
Responsibilities
- Develop and maintain enterprise data products, pipelines, data transformations, and curated datasets for reporting, analytics, automation, machine learning, and GenAI use cases.
- Implement and automate ingestion and transformation of relational, event-based, and unstructured data sources using ETL/ELT tools or scripting languages.
- Develop scalable data storage and processing solutions using distributed and cloud-based platforms.
- Create physical, logical, and conceptual data models and implement data storage architectures according to design guidelines.
- Implement monitoring, alerting, troubleshooting, and data quality controls for data pipelines and data integrity.
- Apply data governance practices for metadata, lineage, access, retention, discoverability, and reusable data assets.
- Translate stakeholder and business requirements into scalable, performant, maintainable, and reusable technical solutions.
- Collaborate with Product Managers, Data Engineers, Data Scientists, Solution Engineers, analysts, business stakeholders, and IT teams.
- Participate in testing, solution validation, documentation, requirements management, and troubleshooting of data pipelines and solutions.
Requirements
- 3 to 6 years of 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 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 scalable, performant, maintainable, and reusable technical solutions.
- Experience working in Agile, cross-functional teams with product, engineering, analytics, and business stakeholders.
- Knowledge or exposure to Big Data technologies, Spark, Scala or Java, Map-Reduce, Hive, HBase, Kafka, clustered cloud computing, large-file movement in cloud environments, analytical solutions, and IoT technology.
- Preferred experience with Data-as-a-Product operating models, data catalogs, data lineage, data quality frameworks, and certified data products.
- Preferred exposure to AI/ML or GenAI initiatives, including AI-ready datasets, semantic models, knowledge assets, or supporting data structures.
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).