Data Engineer
Core
Design, build, and maintain scalable, secure, and high-performance data platforms on AWS, focusing on data pipeline development and analytics enablement.
Role type
Individual contributor data engineer (AWS cloud)
Builds
Cloud-native data lakes, data warehouses, and batch/streaming pipelines
Domain
Cloud data engineering on AWS
Deliverable
production ML models | product features
Required skills
AWS S3, AWS Glue, Amazon Athena, Amazon Redshift, Amazon EMR, SQL, Python, PySpark/Spark, data modeling, performance tuning, Infrastructure as Code (Terraform/CloudFormation), CI/CD pipelines, logging and monitoring (CloudWatch)
Preferred skills
Streaming technologies (Kinesis/Kafka), Lakehouse architectures, BI/reporting tool integration, data governance, metadata management, AWS cost optimization (FinOps), Agile delivery, AI/ML use cases
Technologies
AWS, S3, Glue, Athena, Redshift, EMR, PySpark, Spark, Terraform, CloudFormation, CloudWatch, Kinesis, Kafka
Responsibilities
Design and build scalable ETL/ELT pipelines on AWS; Develop SQL-based data transformations and Python-based data pipelines; Implement data ingestion pipelines using S3, Glue, EMR; Build data models optimized for analytics, performance, and cost efficiency; Support deployment and execution of data pipelines; Monitor pipeline performance, reliability, and data quality; Troubleshoot data issues and perform root cause analysis; Work with architects and product teams to translate business needs into AWS data engineering solutions
Seniority
Mid-level (3-7 years), hands-on IC
