Description

Key Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using Python and Databricks.
• Develop and optimize data workflows within the Databricks architecture (Delta Lake, Spark, notebooks, jobs, clusters, and workspace management).
• Support AI/ML initiatives by preparing high-quality datasets for model training, validation, and deployment.
• Collaborate with data scientists and analytics teams to operationalize machine learning solutions.
• Create and maintain BI dashboards and reports using Power BI, Tableau, and Looker.
• Implement data quality, governance, and performance optimization best practices.
• Work in an Agile/Scrum environment and participate in sprint planning, code reviews, and release activities.
• Troubleshoot production issues and provide ongoing support for data and analytics platforms.

Required Qualifications

• 9+ years of relevant industry experience in Data Engineering / Software Development (excluding training period).
• Minimum 2 years of onsite experience working in a similar technology and domain environment.
• Bachelor’s degree in Technology, Computer Science, Engineering, or a related field.
• Strong programming experience with Python.
• Hands-on experience as a Data Engineer building enterprise-scale data pipelines.
• Deep understanding of Databricks architecture and Apache Spark.
• Experience with Delta Lake, Spark SQL, and distributed data processing.
• Strong knowledge of data warehousing and dimensional modeling.
• Experience integrating data from multiple enterprise systems and APIs.

Must-Have Skills

• Python Programming
• Databricks (Architecture, Spark, Delta Lake)
• AI/ML background (data preparation, feature engineering, model support)
• Power BI
• Tableau
• Looker

Key Skills

Education

Bachelor's degree