Data Engineer: Scalable Pipelines & Data Products

Cummins Inc; Saddar; On-site; PKR 2,500,000 - 4,500,000; Full time

Job summary

Cummins Inc. is seeking a data engineer to support, develop and maintain a data and analytics platform. You will process, store and make data available to analysts, coordinating with Business and IT teams to enable agile data delivery at scale.

You will implement automated deployment of distributed ingestion/transform pipelines, ensure data quality and governance, and build scalable storage across data lakes and cloud platforms. Strong knowledge of ETL/ELT and data modeling is required.

Qualifications

• Bachelor-level degree in a relevant technical discipline or equivalent experience.
• Experience with data integration, ETL/ELT processes and data pipelines.
• Knowledge of data modeling, metadata management and governance.
• Ability to translate requirements into scalable technical solutions.
• Experience working in Agile, cross-functional teams with stakeholders.

Responsibilities

• Develop and maintain enterprise data products by building data pipelines and curated datasets.
• Apply Data-as-a-Product principles to reusable, governed data assets with metadata and quality controls.
• Collaborate with Product, Data Engineers and Analysts to deliver AI-ready data products.
• Implement and automate deployment of distributed data ingestion/transform pipelines.
• Monitor data quality, troubleshoot data integrity issues, and perform testing of pipelines.
• Design and optimize data storage architectures using cloud-based platforms.

Skills

ETL/ELT processes

Data modeling

SQL

Agile

Cloud technologies

SPARK

Scala/Java

Hive

Hbase

Kafka

Education

Bachelor's degree in CS/IT/Engineering

Tools

Data Lakes

Hadoop

HBase

Cassandra

MongoDB

DynamoDB

Job description

Cummins Inc. is seeking a data engineer to support, develop and maintain a data and analytics platform. You will process, store and make data available to analysts, coordinating with Business and IT teams to enable agile data delivery at scale.

You will implement automated deployment of distributed ingestion/transform pipelines, ensure data quality and governance, and build scalable storage across data lakes and cloud platforms. Strong knowledge of ETL/ELT and data modeling is required.