Data Engineering Intern - Summer 2027

addepar1

New York (NY)

Presencial

USD 45.000 - 65.000

Jornada completa

Hace 4 días
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Descripción de la vacante

Addepar is seeking a Data Engineering Intern to join the Portfolio Data Engineering team in New York City for Summer 2027. You will split your time between supporting day-to-day feed maintenance and working on tooling improvements, contributing to the next-generation data pipeline while gaining exposure to production data systems.

The role is full-time in our New York office and requires in-person attendance for the duration of the internship.

Formación

  • Currently enrolled in a university or other post-secondary program.
  • Pursuing a Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related field (penultimate or final year ideal).
  • Able to commit to the full 12-week program, June 7, 2027 - August 27, 2027.
  • Proficiency in Python and SQL.
  • Familiarity with data engineering tools such as ETL pipelines, data warehousing, or Databricks is a plus.

Responsabilidades

  • Support day-to-day maintenance of portfolio data feeds and reconciliation workflows for Enterprise and Hyperscaler clients.
  • Work on tooling improvements that increase pipeline reliability, data quality, and operational efficiency.
  • Contribute to the next-generation data pipeline on well-scoped deliverables.
  • Write well-tested data pipeline code and contribute to process improvements.
  • Collaborate with the Portfolio Data Engineering team and learn from senior engineers.

Conocimientos

Python
SQL

Educación

Bachelor's or Master's in CS/Data Eng/Data Science

Herramientas

ETL pipelines
Databricks
Data warehousing

Descripción del empleo

Who We Are

Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore.

The Program

We are currently seeking a Data Engineering Intern to join our Portfolio Data Engineering team in New York City for Summer 2027.

Being a part of the AddeU Internship Program, you will be working on meaningful project(s) that you can feel proud of and present back to the company at the end of the experience. In addition to having a supporting manager and mentor, we have a fantastic onboarding program to get you acclimated and ready for your time with us. Fun events and super cool swag are also included!

Data is fundamental to everything Addepar does. Our Portfolio Data Engineering team builds and maintains the data pipelines that bring portfolio data into Addepar's platform for our Enterprise and Hyperscaler clients. With enterprise project volume expected to grow significantly over the next year, we are looking for a Data Engineering Intern to help keep those pipelines running smoothly while improving the tooling behind them. If you are excited about working with complex financial data at scale and building more reliable, efficient data pipelines, we want to hear from you!

As a Data Engineering Intern, you will split your time between supporting day-to-day feed maintenance and working on tooling improvements, contributing to the next-generation data pipeline while gaining significant exposure to production data systems.

This role is based full-time in our New York office and requires in-person attendance for the duration of the internship. Relocation assistance is not offered.

Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

What You'll Do
  • Support day-to-day maintenance of portfolio data feeds and reconciliation workflows for Enterprise and Hyperscaler clients
  • Work on tooling improvements that increase pipeline reliability, data quality, and operational efficiency
  • Contribute to the next-generation data pipeline on well-scoped deliverables
  • Write well-tested data pipeline code and contribute to process improvements
  • Collaborate with the Portfolio Data Engineering team and learn from senior engineers
  • Learn and demonstrate data engineering standard processes and principles
  • Produce a retrospective and demonstrate your summer project to an internal audience
Who You Are
  • Currently enrolled in a university or other post-secondary program
  • Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related field (penultimate or final year ideal, though all years are welcome to apply)
  • Able to commit to the full 12-week program, June 7th, 2027 - August 27th, 2027
  • Proficiency in Python and SQL
  • Strong problem-solving skills and attention to data quality
  • Ability to work collaboratively in a team-oriented environment
  • Familiarity with data engineering tools and concepts such as ETL pipelines, data warehousing, or Databricks is a plus

Addepar takes a market-based approach to pay. A successful candidate's starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The range displayed on each job posting reflects the minimum and maximum target base salary for this role within the United States.

Compensation for this role includes base salary + bonus + equity + benefits.

Base Salary Range

$40 - $40 USD

Our Values
  • Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes.
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