Data Engineer: AI-Ready Data Pipelines & Platforms

Cummins Inc; Saddar; On-site; PKR 1,800,000 - 3,600,000; Full time

Job summary

Cummins Inc. in on-site environment seeks a data engineering professional to design, build and operate scalable data pipelines and analytics platforms. You will collaborate with business and IT teams to ingest, store and provision data for analysts and downstream applications.

The role emphasizes data governance, quality and secure data delivery, leveraging Spark, SQL and cloud-based storage to enable agile analytics at scale.

Qualifications

• Experience developing and supporting data integration, ETL/ELT processes, data pipelines, and data transformations.
• Working knowledge of data modeling, SQL, data quality, metadata management, and data governance principles.
• Ability to translate business requirements into scalable, maintainable technical solutions.
• Experience working in Agile, cross-functional teams and collaborating with stakeholders.

Responsibilities

• Develop and maintain enterprise data products by building data pipelines, transformations and curated datasets for reporting and analytics.
• Apply Data-as-a-Product principles to create governed data assets with metadata, lineage and quality controls.
• Collaborate with Product Managers, Data Engineers, Data Scientists and Solution Engineers to deliver AI-ready data products.

Skills

ETL/ELT pipelines

Data modeling

SQL

Agile

Cross-functional collaboration

Education

Bachelor's degree in Computer Science / IT / Engineering / Data Analytics

Tools

Spark

Scala/Java

Hive

Kafka

MapReduce

HBase

Job description

Cummins Inc. in on-site environment seeks a data engineering professional to design, build and operate scalable data pipelines and analytics platforms. You will collaborate with business and IT teams to ingest, store and provision data for analysts and downstream applications.

The role emphasizes data governance, quality and secure data delivery, leveraging Spark, SQL and cloud-based storage to enable agile analytics at scale.