Portfolio Data Engineering Intern

March 19

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Addepar

Addepar is a comprehensive technology and data platform designed to streamline wealth management for investment professionals globally. It empowers firms with sophisticated tools to manage complex investment portfolios, offering features like data aggregation, portfolio trading, portfolio modeling, and fee tracking. With over $6 trillion in assets managed, Addepar serves a variety of financial services including wealth managers, family offices, private banks, and broker-dealers. It supports more than 45 markets worldwide and provides customizable reporting and integration solutions, facilitating better decision-making and client satisfaction.

501 - 1000 employees

Founded 2013

πŸ’Έ Finance

πŸ’³ Fintech

☁️ SaaS

πŸ’° $130M Corporate Round on 2021-11

πŸ“‹ Description

β€’ Working on meaningful project(s) that you can feel proud of and present back to the company at the end of your experience. β€’ Building components within the ETL pipeline that automate cleaning and transformation steps. β€’ Contributing to data pipelines, supporting the ingestion, analysis and enrichment of financial data. β€’ Learning and demonstrating engineering best practices and principles. β€’ Collaborating effectively with product managers, engineers and stakeholders on your project. β€’ Managing individual project priorities, deadlines, and deliverables. β€’ Producing a retrospective and demonstrating your summer project to an internal audience.

🎯 Requirements

β€’ Must be currently enrolled in a post-secondary educational institution (university must be located in Scotland or the UK) & must be returning to school after internship. β€’ Pursuing a degree in computer science, engineering, mathematics or a related technical field. β€’ Available to intern for the full 12 weeks. β€’ Experience with object-oriented programming. β€’ Understanding of data structures and algorithms. β€’ Interest in data modeling, visualization, and ETL pipelines. β€’ General familiarity with some of the technologies we use: Python, Apache Spark / PySpark, Java/Spring, Amazon Web Services, SQL, relational databases. β€’ Knowledge of financial concepts or data systems is a plus. β€’ Excellent written and verbal communication skills.

πŸ–οΈ Benefits

β€’ Fun events and super cool swag are included!

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