Design, implement, and optimize data pipelines in Databricks to process large-scale structured and unstructured data.
Develop ETL workflows for data ingestion, transformation, and integration using Databricks and other cloud-based tools.
Implement Delta Lake for efficient data management and real-time data processing.
Collaborate with data architects and stakeholders to build scalable and reusable data solutions.
Leverage Databricks' MLflow for managing and deploying machine learning workflows, if required.
Ensure data quality, integrity, and compliance with organizational standards and governance policies.

Required Skills & Qualifications:

Education: Bachelor’s or master’s degree in computer science, Data Analytics, Information Technology, or a related field.
Technical Proficiency:

Hands-on experience with Databricks: Spark, Pyspark, Scala, or SQL.
Strong understanding of database concepts and working experience with SQL/NoSQL databases.
Experience integrating Databricks and Power BI with cloud platforms like Azure or AWS.

Analytical Skills: Strong ability to analyse, interpret, and visualize large datasets.
Problem Solving: Demonstrated ability to troubleshoot complex data workflows and reporting challenges.

Soft Skills: Strong written and verbal communication, collaboration, and stakeholder management