AWS Data Engineer
Core
Design, develop, and optimize data pipelines on the AWS ecosystem to provide reliable, secure, and performant data for Data Analysts, Data Scientists, and business teams.
Role type
AWS Data Engineer
Builds
Data pipelines and distributed data processing workflows on AWS
Domain
Cloud Data Engineering (AWS)
Deliverable
production ML models | product features
Required skills
AWS Glue, AWS Lambda, AWS Step Functions, AWS Kinesis, AWS S3, AWS Athena, AWS Redshift, AWS EMR, PySpark, Spark, SQL, Data Lake architecture, Data Warehouse architecture, IAM, KMS, Lake Formation
Preferred skills
Cost optimization, performance tuning, data quality controls, workflow orchestration, technology scouting
Technologies
AWS, PySpark, Spark, Airflow, .Net, Java, Node.js, Python, Power BI, Tableau, Azure Data Factory
Responsibilities
Design, develop, and maintain data pipelines on AWS; Integrate and transform data from diverse sources (SQL/NoSQL databases, APIs, ERPs, CRMs, flat files); Develop distributed and optimized processing using PySpark or Spark on AWS (EMR, Glue); Orchestrate and automate workflows with AWS Step Functions, Managed Airflow, or equivalents; Implement data quality, consistency, and security controls (IAM, KMS, Lake Formation); Optimize processing performance and reduce infrastructure costs; Document pipelines and ensure traceability; Collaborate with Data and IT teams to deliver ready-to-use datasets; Participate in AWS and cloud data solution technology scouting.
Seniority
Mid-level, hands-on IC
