Portfolio Data Engineer

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 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva and São Paulo.

The Role

We’re looking for a Portfolio Data Engineer to join our Data Engineering team in Poland.

A core part of Addepar’s business relies on us being able to quickly and correctly ingest data from a variety of sources, including 3rd party data providers, custodial banks, data APIs, and even direct user input. The data engineers on the Portfolio Data Engineering team help build and maintain the transformation and cleaning steps of our ETL (Extract, Transform, Load) pipeline before it can be stored and accessed by our customers in a standardized fashion. As a data engineer on this team, you’ll be building components within the ETL pipeline that automate these cleaning and transformation steps. As you gain more experience, you’ll contribute to increasingly challenging engineering projects within our broader data infrastructure.

This is a crucial, highly visible role within the company. Your team is a big component of growing and serving Addepar’s client base with minimal manual data cleaning effort required from our clients or from our internal data operations team.

Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position.

What You’ll Do

Complete individual project priorities, deadlines, and solutions.

Build pipelines that support the ingestion, analysis, and enrichment of financial data.

Improve the existing pipeline to increase the throughput and accuracy of data.

Work with data analysts to map general financial concepts to our internal data models in a repeatable and precise fashion.

Understand data models and schemas, and work with other engineering staff to recommend extensions and changes.

Partner with members of Product and Engineering to design, test, and implement new processes and tooling features that improve data quality as well as increase operational efficiency

Who You Are

Ideally you'll have a degree in computer science equivalent experience

Professional software engineering experience

General familiarity with some of the technologies we use:

Python, Apache Spark / PySpark, Java/Spring

Amazon Web Services

SQL, relational databases

Familiarity with relational databases and data pipelines

Expe