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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and optimize scalable ETL/ELT pipelines and data solutions on the Databricks platform, focusing on performance, cost efficiency, and data governance.
Lead end-to-end migration of on-premises SQL Server environments to Databricks Lakehouse, ensuring data transformation, schema conversion, performance tuning, and data integrity.
Develop, deploy, and manage AI/ML pipelines using Databricks capabilities including MLflow, collaborating with data scientists and stakeholders.
Minimum Requirements
5+ years of experience in data engineering with focus on cloud-based data platforms.
Proven hands-on experience migrating complex SQL Server environments to Databricks or similar cloud data warehouses/lakehouses.
Deep expertise in Databricks platform components including Spark, Delta Lake, SQL Analytics, and Databricks Runtime.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related quantitative field.
Ideal Candidate Profile
Strong operational expertise in designing and managing cloud data engineering pipelines with demonstrated success in SQL Server to Databricks migrations.
Experience in integrating AI/ML workflows and MLOps practices within data engineering environments using Databricks and MLflow.
Capability to provide technical leadership and mentoring in a data engineering team, collaborating effectively with cross-functional technical and business teams.