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

- Robust 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.

📌 Databricks (Bengaluru)
🏢 NovBliss
📍 Bengaluru