Aws Data & Analytics Engineer
Core
Design, develop, and optimize scalable data pipelines and modern data solutions on AWS to support organizational analytics and strategic initiatives.
Role type
Senior IC AWS Data & Analytics Engineer
Builds
Scalable data pipelines, Data Lakes, and Data Warehouses on AWS
Domain
Cloud Data Engineering / Analytics
Deliverable
production ML models
Required skills
AWS Data Platform, AWS Glue, PySpark, Amazon Redshift Serverless, Amazon Athena, Amazon S3, Data Modeling (Star/Snowflake Schema), ETL/ELT, SQL, Python, Distributed Processing
Preferred skills
AWS Lake Formation, AWS IAM, AWS CloudWatch, AWS Lambda, Apache Spark, Apache Iceberg, Apache Hudi, Apache Parquet, Apache Airflow, Terraform, AWS CDK, Data Mesh, DataOps
Technologies
AWS Glue, PySpark, Amazon S3, Amazon Redshift Serverless, Amazon Athena, AWS Lake Formation, Apache Spark, Apache Iceberg, Apache Hudi, Apache Parquet, Apache Airflow, Terraform, AWS CDK
Responsibilities
Design and implement data architectures on AWS; Develop ingestion, transformation, and data availability pipelines using AWS Glue and PySpark; Build and maintain Data Lakes using Amazon S3; Develop analytical solutions and Data Warehouses using Amazon Redshift Serverless; Create optimized queries and analytical datasets via Amazon Athena; Implement scalable, resilient ETL/ELT processes; Define and implement dimensional models (Star and Snowflake schemas); Ensure data quality, integrity, consistency, and governance; Optimize performance and costs of AWS data solutions; Troubleshoot issues related to data processing, storage, and querying; Produce technical documentation and promote knowledge transfer; Support corporate data-oriented architectures and Business Intelligence; Participate in architectural definitions and technical reviews.
Seniority
Senior, hands-on IC
