Description

The ideal candidate will have deep expertise in Databricks, strong analytical and problem-solving skills, and the ability to develop and implement scalable data solutions for advanced analytics and machine learning.


 

Key Responsibilities:

Design & Development: Architect and build scalable data pipelines and workflows using Databricks on AWS/Azure/Google Cloud

Data Engineering: Optimize, transform, and cleanse large datasets to enable data-driven insights and decision-making

Integration: Collaborate with data scientists, analysts, and other stakeholders to integrate various data sources into unified solutions

Performance Tuning: Fine-tune and optimize Databricks workflows for performance, scalability, and cost-effectiveness

Automation: Develop reusable frameworks for data processing and implement continuous integration/continuous deployment (CI/CD) workflows

Collaboration: Work with cross-functional teams to understand business requirements and translate them into technical solutions

Documentation: Prepare and maintain technical documentation for data pipelines, workflows, and models

 

Required Skills and Qualifications:

Educational Background: Bachelor's/Master’s degree in Computer Science, Information Technology, or a related field

Experience:

 

5+ years of experience in Databricks and Spark technologies

Hands-on experience with cloud platforms (AWS, Azure, or GCP) 

Proficiency in Python, Scala, or SQL

 

 

 

 

Key Skills
Education

Bachelor’s or Master’s degree

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