Senior AWS Data Engineer

Tasks

• Design and implement scalable data ingestion and transformation pipelines on AWS.
• Build and maintain data lakes using Amazon S3 and analytical platforms such as Amazon Redshift.
• Develop ETL/ELT workflows using Python, SQL, and AWS-native services.
• Model and curate datasets for analytics, reporting, and downstream applications.
• Orchestrate workflows using AWS Step Functions or Apache Airflow.
• Optimize pipeline performance, storage, query efficiency, and cloud costs.
• Implement data quality checks, logging, monitoring, and error handling.
• Apply AWS security practices, including IAM, encryption, and access controls.
• Collaborate with analytics, application, and business teams.
• Maintain reusable code, technical documentation, and engineering standards.

Requirements

• 9+ Years
• AWS Data Engineering, Amazon S3, AWS Glue, Amazon Redshift, Python, SQL, ETL/ELT Pipelines, Data Modeling, Amazon Athena, Amazon EMR, AWS Step Functions/Airflow, Data Lake Architecture.
• 9+ years of professional experience in data engineering or related fields.
• Strong experience building data pipelines on AWS.
• Proficiency in Python and SQL.
• Hands-on experience with Amazon S3, AWS Glue, Redshift, Athena, or EMR.
• Experience developing batch and incremental ETL/ELT pipelines.
• Understanding of data modeling, partitioning, and formats such as Parquet and JSON.
• Experience with AWS Step Functio

Schedule

• W2 Contract
• Hybrid

Location

• Seattle, WA