
Principal Cloud Data Engineer
2 days ago
You will be working closely with data architects, platform engineers, and DevOps teams to build scalable, resilient, and efficient data engineering solutions using modern cloud tools and best practices.
- Design and build scalable ETL/ELT pipelines using cloud-based platforms like Azure Data Factory (ADF) and Azure Databricks.
- Develop and optimize Spark SQL jobs for large-scale batch and streaming data transformations.
- Ingest data from various sources including Apache Kafka, REST APIs, and RDBMS, ensuring real-time or near-real-time availability.
- Implement data modeling strategies for analytics consumption layers in Synapse or ADLS.
- Collaborate with DevOps teams to automate deployment using CI/CD pipelines.
- Monitor, troubleshoot, and optimize data workflows for performance, cost-efficiency, and reliability.
Requirements:
- 5+ years of experience in data engineering roles.
- Hands-on experience with Azure Data Factory (ADF), Azure Databricks, and Apache Kafka.
- Strong skills in SQL, Python, and Spark for data manipulation and transformation.
- Exposure to CI/CD practices and understanding of data lake architecture and modern data warehousing principles.
Responsibilities:
- Participate in sprint ceremonies and contribute to task estimation and delivery planning.
- Support data quality checks, logging, alerting, and observability mechanisms for production workloads.
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