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Senior Data Engineer - AWS
Skills
Continuous Integration And Continuous DeliveryAmazon S3Amazon Web ServicesData GovernanceData MigrationExtractTransform
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Expert-level hands-on experience building production data platforms on AWS
- Proven ability to create end-to-end data pipelines from the ground up
- Hands-on experience designing and building semantic layers in Snowflake
- Track record as a technical subject-matter expert or consultant
- Strong proficiency in PySpark and production ETL/ELT workflows
- Deep knowledge of AWS data services including S3 Lambda Step Functions Glue Athena SNS EventBridge and Lake Formation
- Practical experience with infrastructure-as-code and CI/CD tools including CloudFormation Terraform CDK uDeploy and GitHub
- Experience with large-scale data migrations such as Teradata to S3
- Strong understanding of cost management monitoring and reporting in AWS environments
- Working knowledge of data lake architectures metadata management and data governance
- Bachelor’s degree in a quantitative or technical field
- 7+ years of hands-on data engineering experience with AWS and Snowflake
Nice to have
- Client-focused
- Hands-on
- Self-directed
- Proactive
- Collaborative
- Analytical
- Mentoring mindset
Day to day
- Design and build scalable end-to-end data pipelines on AWS from ingestion through to curated data in Snowflake.
- Develop and optimize production ETL and ELT workflows using PySpark Parquet and Apache Iceberg.
- Act as a hands-on technical subject-matter expert advising client teams and translating complex data engineering concepts into practical solutions.