Roles & Responsibilities:

- Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration of enterprise-wide data from diverse sources.
- Build and optimize data engineering workflows using Databricks and PySpark.
- Write efficient, high-performance SQL for data transformation and analysis.
- Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing, data models, and pipelines.
- Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the development lifecycle.
- Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production environments with proper change control processes.
- Collaborate with cross-functional teams to translate business requirements into scalable data solutions.
- Ensure data quality,



reliability, and performance across all pipelines and platforms.

Required Skills and Qualifications:

- 8 years of overall experience, with strong hands-on experience in Databricks.
- Strong proficiency in PySpark coding.
- Robust hands-on experience in SQL.
- Proficiency in programming languages such as PySpark and Python.
- Experience with Azure Cloud platform and associated services.
- Solid understanding of data warehouse concepts, data modeling, and pipeline design.
- Proven experience providing technical leadership and mentoring developers.
- Hands-on experience with CI/CD implementation using Azure DevOps.
- Strong problem-solving, communication, and stakeholder management skills.

📌 Azure Databricks Developer - Data Engineering (India)
🏢 TalentXO
📍 India