AWS Data Engineer

AI overview

Design and implement data pipelines and data warehousing layers using AWS services while ensuring data accuracy and availability to enhance client analytics capabilities.
  • Design and implement data pipelines using AWS services such as S3, Glue, PySpark and EMR.
  • Develop and maintain data processing and transformation scripts using Python and SQL.
  • Optimize data storage and retrieval using AWS database services such as RDS, Redshift and DynamoDB.
  • Build different types of data warehousing layers based on specific use cases.
  • Utilize expertise in SQL and have a strong understanding of ETL and data modeling.
  • Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their business’s analytics and reporting.
  • 3-8 Years of experience
  • Preference for immediate joiners and candiates who can join us within 30 days 
  • Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, or Information Technology
  • Experience with AWS cloud and AWS services such as S3 Buckets, Glue Studio, Redshift, Athena, Lambda, and SQS queues.
  • Experience with batch job scheduling and identifying data/job dependencies.

Preferred Skills:

  • Proficiency in data warehousing, ETL, and big data processing.
  • Familiarity with the Pharma domain is a plus.

Careers at Datazymes. Find Great Talent with Career Pages. | powered by SmartRecruiters | Find Great Talent with a Career Page.

View all jobs
Ace your job interview

Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.

Data Engineer Q&A's
Report this job
Apply for this job