Databricks

Responsibilities:
Design and implement scalable data platforms and pipelines using Azure Databricks, Apache Spark, Delta Lake, and MLflow.
Lead the migration from legacy platforms to Lakehouse architecture.
Develop batch and streaming data pipelines for ingestion, transformation, and analytics.
Establish standards for data governance, quality, and security.
Collaborate with stakeholders to align architecture with business goals.
Mentor data engineers and developers on Databricks best practices.
Integrate Databricks with tools like Power BI, Tableau, Kafka, Snowflake, and Azure Data Factory.
Mandatory Skills:
Strong command of Databricks and Azure.
Proficiency in SQL, Python, Scala, and Spark.
Experience with CI/CD pipelines, DevOps, and orchestration tools like Airflow or Data Factory.
Familiarity with Azure cloud platforms.
Deep understanding of distributed computing, performance tuning, and data security.
Preferred Skills:
Experience with data mesh, data fabric, or enterprise data architectures.
Strong ERP knowledge (e.g., SAP, Salesforce).
Hands-on capability and self-exploration skills to drive analytics adoption across business teams.

Work arrangement
Yes