Design, build, and maintain scalable data platforms using AWS to support analytics, machine learning, and emerging generative AI use cases
Collaborate with data scientists, analysts, and engineering teams to translate business and AI requirements into scalable data solutions
Ensure data quality, performance, and cost efficiency across the platform
Work with large-scale datasets to build and optimize data pipelines using AWS services such as EMR (Spark, Trino), S3, Glue, Athena, and Airflow
Design and manage lakehouse architectures, using technologies like Apache Iceberg and Glue Catalog
Support machine learning and LLM projects by preparing and delivering datasets for use in Amazon SageMaker and Amazon Bedrock

Requirements

3+ years of experience in data engineering or related roles
3+ years experience with Python and SQL
3+ years hands-on experience with cloud platforms (AWS, Azure, or GCP)
Experience building and maintaining scalable batch data pipelines
Experience working with data lakes or lakehouse architectures
Experience with Apache Spark and EMR
Bachelor's degree in Computer Science, Engineering, Mathematics, or related discipline

Benefits

Great compensation package and bonus plan
Core benefits including medical, dental, vision, and matching 401K
Flexible work environment, ability to work remote, hybrid or in-office
Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringPythonSQLAWSApache SparkEMRdata pipelinesdata lakeslakehouse architecturesmachine learning

Soft Skills

collaborationcommunicationproblem-solvinganalytical thinking