About the Role
We are looking for a skilled Data Engineer to design, build, and maintain scalable data solutions on the Azure platform. You will play a pivotal role in developing robust data pipelines, ensuring data quality, and driving enterprise-wide analytics initiatives across a high-impact global team.
Key Responsibilities
- Design and develop scalable data pipelines using Spark SQL and PySpark on Azure Databricks
- Build and orchestrate ETL workflows using Azure Data Factory (ADF)
- Develop and maintain a modern Lakehouse architecture leveraging ADLS and Databricks
- Perform data preparation tasks including cleaning, normalization, deduplication, and type transformations
- Collaborate with DevOps teams to deploy and manage production-grade data solutions
- Monitor pipelines, identify issues, and drive root cause analysis and resolution
- Contribute to a global Analytics team, delivering data-driven insights and scalable solutions
- Partner with Data Science and BI teams to share best practices and foster innovation
- Lead data engineering projects and support cross-functional initiatives
- Apply change management practices — including documentation, communication, and training — for system upgrades and data migrations
Requirements
Must-Have Skills
- Minimum 6 years of experience in Data Engineering
- Strong hands-on experience with the Azure ecosystem — Azure Databricks, Azure Data Factory (ADF), ADLS
- Proficiency in PySpark and Spark SQL
- Solid understanding of ETL processes and data pipeline development
- Advanced SQL skills