A leading technology firm is seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines. The ideal candidate will have strong skills in Python and PySpark, proven experience with a variety of AWS services, and solid SQL abilities. Responsibilities include building ETL pipelines, ensuring data quality, and collaborating with stakeholders. This full-time position is perfect for someone looking to leverage their AWS knowledge in a dynamic environment.
Qualifications
Strong experience with Python and PySpark for large-scale data processing.
Solid SQL skills and familiarity with data modeling and query optimization.
Experience with ETL best practices, data quality checks, and monitoring/alerting.
Familiarity with version control (Git) and basic DevOps/CI-CD workflows.
Responsibilities
Build and maintain ETL pipelines using Python and PySpark on AWS.
Orchestrate workflows with AWS Step Functions and serverless components.
Implement messaging and event-driven patterns using AWS SNS and SQS.
Design and optimize data storage and querying in Amazon Redshift.
Ensure data quality, monitoring, error handling and operational support for pipelines.
Collaborate with data consumers and stakeholders to translate requirements into solutions.
Contribute to CI/CD, infrastructure-as-code, and documentation for deployments.
Skills
Python
PySpark
AWS Lambda
AWS SNS
AWS SQS
AWS Glue
AWS Redshift
SQL
Version control (Git)
CI/CD workflows
Job description
A leading technology firm is seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines. The ideal candidate will have strong skills in Python and PySpark, proven experience with a variety of AWS services, and solid SQL abilities. Responsibilities include building ETL pipelines, ensuring data quality, and collaborating with stakeholders. This full-time position is perfect for someone looking to leverage their AWS knowledge in a dynamic environment.