17 days ago
Pune, IndiaSenior
Responsibilities
- Design, build, optimize, and operate reusable data pipelines, data transformations, curated data assets, and domain-aligned data products.
- Automate ingestion and transformation of relational, event-based, and unstructured data sources using ETL/ELT tools or scripting languages.
- Design and implement data quality, data integrity, monitoring, alerting, metadata, lineage, retention, access, and governance processes.
- Develop physical data models, optimize database indexing and table relationships, and support scalable data architectures.
- Build distributed and cloud-based data storage and processing solutions for analytics, reporting, APIs, automation, and AI/ML use cases.
- Prepare AI-ready datasets, semantic models, vectorized content, and trusted knowledge sources for GenAI and intelligent business solutions.
- Translate stakeholder and product requirements into maintainable, performant, scalable technical solutions.
- Test, troubleshoot, document, and validate data pipelines and solutions against quality and customer requirements.
- Collaborate with cross-functional Agile teams and mentor less experienced team members.
- Support automation and modernization of data management and integration infrastructure.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related technical discipline, or equivalent practical/relevant experience.
- Intermediate experience in data engineering or a relevant discipline, including enterprise data pipelines, transformations, integration solutions, and large-scale data processing.
- Experience with data modeling, SQL development, data quality validation, performance optimization, and scalable data architecture.
- Experience with modern cloud data platforms, data warehouses, ETL/ELT technologies, and clustered cloud-based computing.
- Experience with big data platforms and tools such as Spark, Scala or Java, MapReduce, Hive, HBase, and Kafka, or equivalent coursework.
- Experience developing cloud-based applications involving large file movement and extracting data from varied sources.
- Ability to analyze complex business systems, industry requirements, data regulations, and large datasets.
- Experience building analytical solutions and collaborating with Product Managers, Data Scientists, architects, Solution Engineers, and business stakeholders.
- Preferred experience with Data-as-a-Product practices, data cataloging, lineage, metadata management, certification, and governance.
- Preferred exposure to GenAI, AI/ML, retrieval-augmented generation, vector databases, semantic search, knowledge management, IoT, or AI-ready data engineering.
- Experience with Agile software development 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).