Addepar

Finance / FinServ

DataEngineer

edinburgh, scotland, united kingdom
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Engineer at Addepar. Skills: Data Engineering, PySpark, Databricks, SQL, Data Modeling, ETL. Execute the development of new data integrations. Maintenance of existing processes”

Industry & Context.

Finance / FinServ
Problems you'll solve

Solving previously intractable problems

Eligibility Requirements

Must have, and maintain, the right to work in the United Kingdom from the first day of employment, Visa sponsorship is not available

What They're Looking For.

Must Have

Prior professional data engineering/analysis experience, Experience with object-oriented programming (we use PySpark/Python), Knowledge of SQL or relational database concepts, Experience in data modeling, visualization, and ETL pipelines, Comfort working with AI/LLM tools as part of your development workflow, Ability to work in the United Kingdom

Nice to Have

Knowledge of financial concepts, Passion for the world of FinTech

What You'll Do.

Execute the development of new data integrations

Maintenance of existing processes

Expand and improve our data platform

Add automation and functionality to distributed data pipelines

Write PySpark code and integrate it within our Databricks Data Lake

Contribute to engineering projects

Increase the throughput of data ingestion

Build pipelines that support the ingestion

and enrichment of financial data

Improve existing pipelines

Develop and maintain efficient process controls and accurate metrics

Identify areas of automation opportunities and implement improvements

Understand data models and schemas

Recommend extensions and changes to data models and schemas

Use AI-assisted development workflows

Maintain and improve automated quality gates

How You'll Work.

Team & Collaboration

Partner with members of Product and Engineering to design, test, and implement new processes and tooling features; Work with other engineering teams to recommend extensions and changes to data models and schemas

Process & Methodology

Complete individual project priorities, deadlines, and solutions

Full Job Description

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 Portfolio Data Integration is part of the broader Addepar Platform team. The overall Addepar Platform provides a single source of truth “data fabric” used by the Addepar product set, including a centralized 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, modeling, tooling and infrastructure related to the integration of client portfolio data. Addepar’s 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 engineer for this team, you will execute the development of new data integrations and maintenance of existing processes in order to expand and improve our data platform. You’ll be adding automation and functionality to our distributed data pipelines by writing PySpark code and inte

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