3 days ago
Pune, IndiaStaff+
Responsibilities
- Develop and maintain enterprise data products, pipelines, transformations, and curated datasets.
- Implement ETL/ELT processes for relational, event-based, and unstructured data sources.
- Build scalable distributed and cloud-based data storage and processing solutions.
- Apply Data-as-a-Product principles, including metadata management, lineage, discoverability, governance, and quality controls.
- Monitor and troubleshoot data quality, data integrity, pipeline performance, and system issues.
- Develop physical data models and data storage architectures according to design guidelines.
- Translate stakeholder and product requirements into scalable, maintainable, and reusable technical solutions.
- Collaborate with product, engineering, analytics, data science, solution engineering, and business teams.
- Support AI-ready datasets, semantic models, knowledge assets, and data structures for ML and GenAI applications.
- Perform programming, solution validation, testing, documentation, requirements analysis, and problem solving.
Requirements
- Relevant college, university, or equivalent technical degree, with a bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related field listed as a qualification.
- Equivalent relevant or practical experience may substitute for the degree requirement.
- Experience developing and supporting data integration, ETL/ELT processes, data pipelines, data transformations, and modern cloud-based data platforms.
- Working knowledge of data modeling, SQL, data quality, metadata management, and data governance.
- Ability to translate business and product requirements into efficient technical solutions with attention to scalability, performance, maintainability, and reuse.
- Experience working in Agile, cross-functional teams with product, engineering, analytics, and business stakeholders.
- Preferred exposure to data catalogs, lineage, data quality frameworks, certified data products, Data-as-a-Product operating models, AI/ML initiatives, and GenAI data preparation.
- Preferred knowledge or exposure to Big Data technologies, Spark, Scala or Java, MapReduce, Hive, HBase, Kafka, clustered cloud computing, large-file cloud movement, analytical solutions, and IoT technology.
- Relevant temporary student employment, internship, co-op, or extracurricular team experience is preferred.
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).