Job Description:
We are seeking skilled and dynamic Cloud Data Engineers specializing in AWS, Azure, Databricks. The ideal candidate will have a strong background in data engineering, with a focus on data ingestion, transformation, and warehousing. They should also possess excellent knowledge of PySpark or Spark, and a proven ability to optimize performance in Spark job executions.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines for a variety of cloud platforms including AWS, Azure, Databricks.
- Implement data ingestion and transformation processes to facilitate efficient data warehousing. - Utilize cloud services to enhance data processing capabilities:
- AWS: Glue, Athena, Lambda, Redshift, Step Functions, DynamoDB, SNS.
- Azure: Data Factory, Synapse Analytics, Functions, Cosmos DB, Event Grid, Logic Apps, Service Bus.
- Optimize Spark job performance to ensure high efficiency and reliability. - Stay proactive in learning and implementing new technologies to improve data processing frameworks. - Collaborate with cross-functional teams to deliver robust data solutions. - Work on Spark Streaming for real-time data processing as necessary.
Qualifications:
- 3-8 years of experience in data engineering with a strong focus on cloud environments. - Proficiency in PySpark or Spark is mandatory. - Proven experience with data ingestion, transformation, and data warehousing. - In-depth knowledge and hands-on experience with cloud services(AWS/Azure): - Demonstrated ability in performance optimization of Spark jobs. - Strong problem-solving skills and the ability to work independently as well as in a team. - Cloud Certification (AWS, Azure) is a plus. - Familiarity with Spark Streaming is a bonus.
Keyskills: AWS OR Azure Azure Data Engineer OR AWS Data Engineer Azure AWS
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