Apprenticeship, Data Engineer at Flatiron School

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

23.0

Posted On

22 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Python, SQL, AWS, APIs, Machine Learning, Agile Development, Problem Solving, Collaboration, Documentation, Debugging, Data Pipelines, Business Intelligence, Curiosity, Initiative, Accountability

Industry

Description

About the role Flatiron School is offering a part-time, paid apprenticeship for a data engineer eager to gain real-world experience while growing their skill set across disciplines. This unique program combines part-time hands-on project work with a part-time, fully funded enrollment in Flatiron’s AI and Machine Learning part-time bootcamp course, valued at $14,900 in tuition costs. As a data engineer apprentice, you’ll maintain data pipelines, automate workflows, collaborate with experienced engineers, and build your portfolio with production-ready work. At the same time, you’ll deepen your understanding of data and machine learning to become a more versatile, well-rounded AI Product Engineer. This is a full-time opportunity, 40 hours/week (20 hours coursework and 20 hours apprentice work) for a 14 month program. This is a hybrid role requiring one day week in person in NYC. Whether you’ve completed a coding bootcamp or a Computer Science degree, this opportunity is designed to help you grow as both an engineer and a builder with cross-functional insight. What you'll do Attend and complete the Flatiron School Advanced AI & Machine Learning bootcamp as part of the apprenticeship (tuition waived) Assemble and maintain clean data sets trusted and relied upon by every member of the organization for mission-critical decision-making Write clean, maintainable and testable code using modern frameworks and tools Support debugging, documentation, and QA processes Collaborate on development of Flatiron School’s educational platform Receive ongoing mentorship from senior developers and product leaders What you'll learn How engineering and data intersect in modern AI products How to prioritize with real stakeholder needs and business strategy in mind Practice agile development workflows in a collaborative environment Best practices for writing clean, maintainable, production-quality code How to apply software engineering principles to data challenges Qualifications Requirements: Must be able to work in person in NYC at least one day a week Must be currently living in the U.S. Must be authorized to work in the U.S. We do not offer any visa sponsorship at this time Must be available 40 hours/week to complete the Flatiron School Advanced AI and Machine Learning bootcamp and for apprenticeship work Have a Bachelor’s in computer science or related field or completed a software engineering bootcamp Successfully complete the Flatiron School Aptitude Assessment Candidates must submit a cover letter with their application explaining why they're interested in the program as well as a link to their professional work. Preferred Skills: Experience automating data pipelines and building data sets via third-party APIs Advanced SQL knowledge and experience working with relational databases Proficient in Python Experience with AWS cloud services: Lambda, Redshift, API Gateway Experience with business intelligence tools like Looker or Tableau Strong problem-solving skills related to working with unstructured datasets Comfortable working cross-functionally with non-technical stakeholders Accountability in managing time and meeting small milestones Curiosity, initiative, and a strong desire to grow into a multidisciplinary developer Compensation & Commitments Hourly Pay: $23 hour (20 hours/week) plus $14,900 tuition waiver for bootcamp 14 month commitment Hours: 40 hours per week total - 20/week in apprenticeship role, 20/week in part-time bootcamp courses

Responsibilities

As a data engineer apprentice, you will maintain data pipelines, automate workflows, and collaborate with experienced engineers. You will also build your portfolio with production-ready work while deepening your understanding of data and machine learning.