Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Mid-level, generalist data role in metro with broad AWS skillset increases candidate competition.
Cloud-native data engineering skills (AWS Glue, Redshift, Python) are highly transferable across industries.
Explicit 4–6 years plus required AWS Glue, Redshift, Python and cloud experience increases shortlisting strictness.
Design, develop, and maintain scalable data ingestion, transformation, and processing pipelines using AWS services including AWS Glue, Lambda, Redshift, Snowflake, RDS, and DynamoDB.
Ensure data quality, integrity, security, governance, and reliability across cloud data platforms while optimizing architecture for scalability, performance, and cost efficiency.
Collaborate with cross-functional teams to deliver business-focused data solutions and continuously monitor and enhance production data workflows.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related technical field.
4–6 years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
Hands-on experience with AWS data and analytics services including AWS Glue, Amazon Redshift or Snowflake, Amazon RDS, Amazon DynamoDB, and AWS Lambda.
Proficiency in Python, strong SQL skills, and understanding of data modeling principles.
Experienced with large-scale cloud data pipelines and enterprise data warehousing using AWS services and Snowflake.
Comfortable working in Agile, DevOps-oriented environments with cross-disciplinary collaboration.
Has familiarity with modern cloud data ecosystems, infrastructure as code (e.g., Terraform, CloudFormation), and implementation of data governance and security best practices.