Databricks Data Engineer

About the role:

Data Engineer

Key Responsibilities:

• Develop and maintain

  data pipelines

  using

  PySpark

  on

  Databricks

  .
• Design and implement

  ETL workflows

  for large-scale data processing.
• Optimize Spark jobs for performance and cost efficiency.
• Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions.
• Ensure data quality, integrity, and security across all processes.
• Work with

  Delta Lake

  ,

  SQL

  , and

  data lake architectures

  for structured and semi-structured data.
• Monitor and troubleshoot production data pipelines and workflows.
• Document processes and maintain best practices for data engineering.

Required Skills Qualifications:

• 3-5 years

  of experience in

  data engineering

  or related roles.
• Strong proficiency in

  PySpark

  and

  Spark SQL

  .
• Hands-on experience with

  Databricks

  platform.
• Solid understanding of

  data lake

  ,

  Delta Lake

  , and

  distributed computing

  concepts.
• Experience with

  cloud platforms

  (Azure, AWS, or GCP) and their data services.
• Proficiency in

  SQL

  and working with relational databases.
• Familiarity with

  CI/CD pipelines

  and version control (Git).
• Strong problem-solving and debugging skills.

Why Join Exponentia.ai

• Innovate with Purpose:

  Opportunity to create pioneering AI solutions in partnership with leading cloud and data platforms

• Shape the Practice:

  Build a marquee capability from the ground up with full ownership

• Work with the Best:

  Collaborate with top-tier talent and learn from industry leaders in AI

• Global Exposure:

  Be part of a high-growth firm operating across US, UK, UAE, India, and Singapore

• Continuous Growth:

  Access to certifications, tech events, and partner-led innovation labs

• Inclusive Culture:

  A supportive and diverse workplace that values learning, initiative, and ownership.