AWS Data Engineer

- Design, build, and maintain scalable data pipelines for a variety of cloud platforms including AWS.

- 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.

- 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:

 5-8 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): - 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) is a plus. - Familiarity with Spark Streaming is a bonus.