Data Engineer

As an engineer at Amplify, you will join a talented team solving the toughest problems in education with the best ideas in technology – including user experience, APIs and services, data analysis, and deployment pipelines. You’ll play an active role in imagining and improving product design and the classroom experience.

Essential Responsibilities:

Our data team builds, augments, and maintains the infrastructure that empowers teams across Amplify and our customers to make sense of and tell stories with their data. We believe strongly in teaching our teammates to serve themselves, within a safe, reliable, and agile environment. You’ll be building data systems, but also the sharing-and-learning culture so that every team uses these tools to improve their own lives, and those of our students and teachers. 

• Impress the toughest customers around – students – by:

  • helping teams create fun, compelling apps by using millions of data points

• Make life better for passionate teachers by:

  • helping teachers understand their students by building reusable data pipelines

• Make life better for passionate Data Science, Governance and Analyst teams by:

  • Implementing and managing data storage solutions (e.g., data lakes, databases).

  • Building and maintaining ETL & machine learning pipelines on AWS

  • Collaborating with data scientists and analysts to facilitate data access and utilization.

  • Ensuring data privacy and compliance with relevant regulations.

  • Analyzing and improving performance and squashing tricky bugs using tools like: Snowflake, Airflow, dbt, SQL, Python, Looker, Terraform, and Datadog

• Learn every day by:

  • immersing oneself in agile rituals and using our infrastructure

  • leading collaboration, pull request-ing, and mentoring on a multi-functional team

  • participating in cross-team share-outs, brown bags, and workshop series

  • becoming an expert in the data models and standards within Amplify and the educational industry in order to deliver quality and consistent solutions

Example Projects You Might Work On

• Building well-tested and optimized ETL data pipelines for both full and delta extraction

• Collaborating with data analysts and learning scientists to gather, design, and implement ETL and Data Warehousing requirements

• Contributing to leading industry data standards (Caliper Analytics or xAPI), communities or open source projects (dbt)

• Build and support a machine learning model pipeline from development through production deployment

Required Qualifications: 

• BS in Computer Science, Data Science, or equivalent

• 2+ years of professional software development, site reliability, devops, or data engineering experience

• Strong CS and data engineering fundamentals

• Proven fluency in SQL and a development language such as Python

• Understanding of ETL/ELT pipelines and Data Warehousing design, tooling, and support

• Understanding of different data formatting (JSON, CSV, XML) and data storage techniques (3NF, EAV Model, Star Schema, Data Lake)

• Strong communication skills in writing and conversation

Preferred Qualifications: 

• Experience with MLOps tooling such AWS Sagemaker, GCP Vertex AI and frameworks like Pytorch or Tensorflow

• Experience with tools we use every day:

• Storage: Snowflake, AWS Storage Services (S3, RDS, Glacier, DynamoDB)

• ETL/BI: Cube, dbt, Fivetran, Looker

• Cloud Infrastructure: AWS/GCP/Azure, Terraform

• Experience with tools we don’t use, but should

• Proven passion and talent for teaching fellow engineers and non-engineers

• Proven passion for building and learning: open source contributions, pet projects, self-education, Stack Overflow

• Experience in education or ed-tech