Databricks Data Engineer

Quick Facts

• Role: Databricks Data Engineer

• Focus: Building a modern, scalable data platform for analytics, machine learning, and AI use cases

Description

You’ll design, build, and maintain scalable data pipelines using Databricks and Apache Spark. The role includes integrating data from multiple sources, optimizing large-scale data processing, and supporting a unified lakehouse and cloud data architecture. You’ll collaborate with Data Scientists, Analysts, and business stakeholders to deliver data products for ML, BI, and analytics.

Responsibilities

• Design, build, and maintain scalable data pipelines with Databricks and Apache Spark

• Integrate data from multiple sources into reliable, reusable data flows

• Develop and optimize data processing solutions for large volumes of data

• Deliver data products supporting ML, BI, and analytics in collaboration with stakeholders

• Contribute to a unified data platform and high-quality data layer

• Ensure pipelines are reliable, scalable, performant, and easy to maintain

• Optimize performance, scalability, and cost efficiency of processing and infrastructure

• Implement and maintain data quality, monitoring, and data engineering best practices

• Support the evolution of modern lakehouse and cloud data architectures

Requirements

• Hands-on experience with Databricks

• Strong experience in Data Engineering and production-grade data pipelines

• Strong SQL and PySpark/Apache Spark skills

• Experience with large datasets and distributed data processing

• Understanding of modern data platform, lakehouse, and data architecture concepts

• Experience with cloud environments such as Azure, AWS, or GCP

• Ability to work with different data sources, formats, and integration patterns

• Ability to work closely with Data Scientists, Analysts, and other stakeholders to understand data requirements

Benefits

Join a large-scale data & AI transformation and build the data foundations that power analytics, machine learning, and AI use cases with modern Databricks and lakehouse architecture.