
Senior Cloud Data Engineer
2 weeks ago
Job Summary:
A seasoned data engineering professional with 6+ years of experience in designing, developing, and optimizing ETL/ELT data pipelines using Apache Spark (PySpark or Scala), AWS Glue, and Azure Data Factory is required for this role.
The ideal candidate will collaborate with cross-functional teams to build scalable ingestion and transformation workflows across cloud platforms. They will work with structured and unstructured data to support advanced analytics, reporting, and ML workflows.
Key Responsibilities:
- Design, develop, and optimize ETL/ELT data pipelines using Apache Spark (PySpark or Scala), AWS Glue, and Azure Data Factory
- Collaborate with data scientists, analysts, and application developers to support advanced analytics, reporting, and ML workflows
- Work with structured and unstructured data to build scalable ingestion and transformation workflows across cloud platforms
- Implement job orchestration, monitoring, and error handling for reliable pipeline execution
- Maintain and support existing data pipelines
- Data load monitoring and validation
- Investigate and resolve dependencies, failures, and configuration issues in Glue workflows
- Tune job configurations for optimal performance
- Perform impact analysis and root cause analysis as needed
Required Skills and Qualifications:
This position requires a strong understanding of cloud-based data processing technologies, including Apache Spark, AWS Glue, and Azure Data Factory. The ideal candidate will have experience with data engineering principles, data modeling, and data visualization tools. A bachelor's degree in Computer Science, Information Technology, or a related field is preferred.
Benefits:
This role offers a competitive salary, comprehensive benefits package, and opportunities for career growth and development. We are an equal opportunity employer committed to diversity and inclusion.
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