Data Engineer

Role Overview

As a Data Engineer at Amplify (full remote), you will build and maintain data systems and storage solutions. You’ll collaborate with data scientists and analysts to make data accessible, reliable, and compliant—while also mentoring teammates and contributing to shared technical standards.

Key Missions

• Build, improve, and maintain the data infrastructure to help teams understand and communicate insights.
• Implement and manage data storage solutions.
• Build and maintain ETL and machine-learning pipelines on AWS.
• Partner with data scientists and analysts to enable data access and usage.
• Ensure compliance with regulations and support shared data models/standards in education.

Responsibilities

• Develop and operate data pipelines and data storage architecture.
• Support data modeling practices and standards.
• Communicate effectively with technical and non-technical stakeholders.
• Participate in cross-team share-outs and mentoring/teaching.

Requirements

• Fluency in SQL and a development language such as Python.
• 2+ years of professional experience in software development, site reliability, DevOps, or data engineering.
• Understanding of ETL/ELT pipelines and data warehousing design.
• Strong written and verbal communication skills.
• BS in Computer Science, Data Science, or equivalent.
• Solid fundamentals in data engineering.
• Experience with data formats: JSON, CSV, XML.
• Familiarity with data storage/models such as 3NF, EAV, Star Schema, Data Lake.

Nice-to-haves

• MLOps experience with AWS SageMaker, GCP Vertex AI and frameworks such as PyTorch or TensorFlow.
• Experience with storage platforms: Snowflake, and AWS services (S3, RDS, Glacier, DynamoDB).
• Experience with ETL/BI tooling: Cube, dbt, Fivetran, Looker.
• Experience with cloud infrastructure and IaC: AWS/GCP/Azure and Terraform.
• Teaching/mentoring mindset and a strong commitment to learning (open source, pet projects, self-education).
• Experience in education / ed-tech.