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Über
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
What we offer:
Salary is only one component of the Amplify Total Rewards package, which includes a 401(k) plan, competitive health insurance and mental health options, basic life insurance, paid time off, parental leave, and access to best-in-class development programs. The gross salary range for this role is $135,000 - $155,000. This role is eligible to earn an annual discretionary bonus that rewards individual and company performance. Amplify is an Equal Opportunity Employer. Amplify makes employment decisions based on qualifications and merit, and does not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, veteran status, or any other legally protected characteristic or status. Amplify is committed to providing reasonable accommodations for qualified individuals with disabilities, including disabled veterans. If you have a disability and need an accommodation in connection with the application or hiring process, please email hiringaccommodations@amplify.com. . If you are selected for employment, a background check will be required. As required by state and local laws and district policies, you may be required to provide additional documentation, such as proof of vaccination, or submit to enhanced background screening, such as fingerprinting. Amplify is an E-Verify participant.
Sprachkenntnisse
- English
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