Data Engineer - ML Production & AWS Data Pipelines

Relha LLC; Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon's PXTCS team is looking for a Data Engineer to design and optimize data architectures, standardize metrics, and translate analytics into production-ready solutions. You will build scalable data pipelines using AWS, create APIs for model serving, and collaborate with economists, data scientists, and software engineers to deliver impact at scale across multiple AWS accounts.

You will work with engineers and scientists to productionize models, maintain data systems, and drive reliable,

Qualifications

• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• 3+ years of data engineering experience
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Responsibilities

• Data Pipeline Development: Design and maintain scalable data pipelines using native AWS services (Glue, EMR, Lambda); build monitoring and error handling for data workflows; optimize performance, reliability, and cost efficiency
• Model Productionization & API Development: Develop and maintain APIs and data serving layers that productionize science models for downstream consumption; build batch and real-time inference pipelines
• Data Integration & Quality: Build scalable feature extraction and processing frameworks for diverse data types; develop robust data quality and validation checks; create flexible schemas supporting evolving requirements
• Cross-team Collaboration: Partner with economics, data science, and software engineering teams to translate analytical requirements into production-ready solutions; participate in technical design reviews and architecture discussions
• Analytics & Infrastructure: Maintain layered data systems used by economists and scientists; build automated reporting solutions; work across multiple interconnected AWS accounts with security best practices

Skills

Data Engineering

Python/Java/Scala/NodeJS

ETL pipelines

AWS data services

NoSQL/databases

Tools

Hadoop

Hive

Spark

EMR

Redshift

Kinesis

Lambda

Job description

Amazon's PXTCS team is looking for a Data Engineer to design and optimize data architectures, standardize metrics, and translate analytics into production-ready solutions. You will build scalable data pipelines using AWS, create APIs for model serving, and collaborate with economists, data scientists, and software engineers to deliver impact at scale across multiple AWS accounts.

You will work with engineers and scientists to productionize models, maintain data systems, and drive reliable,