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.

We are seeking an experienced and highly motivated Data Engineering Manager to lead Portfolio Data Engineering, a critical component of the Addepar Platform team. The overall Addepar Platform provides a single source of truth “data fabricˮ used by the Addepar product set, including a centralised and self-describing repository (a.k.a Data Lake), a set of API-driven data services, an integration pipeline, analytics infrastructure, warehousing solutions, and operating tools. The team has responsibility for all data acquisition, conversion, cleansing, disambiguation, modelling, tooling and infrastructure related to the integration of client portfolio data. Addeparʼs core business relies on the ability to quickly and accurately ingest data from a variety of sources, including 3rd party data providers, custodial banks, data APIs, and even direct user input. Portfolio Data integrations and feeds are a highly critical cross-section of this set, allowing our users to get automatically updated and reconciled information on their latest holdings onto the platform. As a Data Engineering Manager, you will play a crucial role in leading and managing our engineering efforts, collaborating closely with product counterparts in an agile environment to drive business outcomes. Your responsibilities will include leading a team to deliver complex engineering projects with the ultimate goal of dramatically increasing the throughput of data ingestion for Addepar. Youʼll be adding automation and functionality to our distributed data pipelines by writing PySpark code and integrating it within our Databricks Data Lake. Your team is a big component of growing and serving Addeparʼs client base with minimal manual effort required from our clients or from our internal data operations team. This is a crucial, highly visible role within the company. Your team is a big component of growing and serving Addeparʼs client base with minimal manual data cleaning effort required from our clients or from our internal data operations team. Please note: applicants must have, and maintain the right to work in Poland to be considered. A background check is required to be completed prior to the first day of work.

• Serve as a "player/coach" who will contribute to and supervise a team of Portfolio Data Engineers in Poland. • Drive the technical direction for the portfolio data engineering team in Poland in close alignment with your direct peers in other regions and the wider engineering community • Build and manage a team of exceptional engineers • Partner with multi-functional teams to design, develop, and deploy scalable data solutions that meet client requirements on time • Lead a team to build pipelines that support the ingestion, analysis, and enrichment of financial data by collaborating with business data analysts • Advocate for standard methodologies, find opportunities for automation and optimisations in code and processes to increase the throughput and accuracy of data • Develop and maintain efficient process controls and accurate metrics that improve data quality as well as increase operational efficiency • Working in a fast-paced, dynamic environment to deliver high-quality results and drive continuous improvement

• Proven experience leading data engineering teams, several years of professional data engineering experience as an individual contributor • A computer science degree or equivalent experience • Strong problem-solving and decision-making skills • Working knowledge of at least one object oriented programming language (PySpark, Python, Java), relational databases, SQL and data pipelines • Knowledge of financial concepts (e.g., stocks, bonds, etc.) is helpful but not necessary • Passion for the world of FinTech and solving previously intractable problems at the heart of investment management is a plus