Staff Software Engineer - Data Platform Edinburgh, UK

Tbwa Chiat/Day Inc
Basingstoke
4 days ago
Create job alert

Addepar is a global technology and data company that helps investment professionals provide the most informed, precise guidance for their clients. Hundreds of thousands of users have entrusted Addepar to empower smarter investment decisions and better advice over the last decade. With client presence in more than 45 countries, Addepar’s platform aggregates portfolio, market and client data for over $7 trillion in assets. Addepar’s open platform integrates with more than 100 software, data and services partners to deliver a complete solution for a wide range of firms and use cases. Addepar embraces a global flexible workforce model with offices in Silicon Valley, New York City, Salt Lake City, Chicago, London, Edinburgh and Pune.

The Role

The Precompute Platform team is seeking a senior backend engineer (II) to join the team. The team is core to achieving Addepar's transition to using next generation tools and processes for data and analytics with a scalable global operating model. The team's mission is to empower analysts, researchers, and other internal teams to performantly generate data and analytics artifacts. We operate on Terabyte-scale datasets, and enable second to sub-second performance by leveraging vector-oriented programming and distributed systems.

What You’ll Do

  • Architect, implement, and maintain engineering solutions to solve sophisticated problems; write well-designed, testable code
  • Work in partnership with product managers and technology partners to map out solutions for challenging technology and workflow problems
  • Gain foundational knowledge of core Addepar systems, including the Addepar Data Lakehouse. Use these insights to work with counterparts. Drive opportunities to improve the end-user experience
  • Reduce complexity through the adoption of strategic data architecture and workflows
  • Communicate technical ideas and set direction on projects with a focus on solving business challenges
  • Mentor other engineers on the team

Who You Are

  • B.S., M.S., or Ph.D. in Computer Science or similar technical field (or equivalent practical experience)
  • Experience in building and evolving large-scale, high-performing distributed systems
  • 6+ years experience as a professional software engineer, primarily in Python
  • Experience with vector-oriented development (NumPy, PyArrow, Dask, Spark are preferred, but we are open to candidates with experience of other vector languages)
  • Strong AWS knowledge and architectural experience
  • A confident and positive outlook with low ego; high degree of ingenuity, resourcefulness, and problem-solving skills

Our Values

  • Act Like an Owner -Think and operate with intention, purpose and care. Own outcomes.
  • Build Together -Collaborate to unlock the best solutions. Deliver lasting value.
  • Champion Our Clients -Exceed client expectations. Our clients’ success is our success.
  • Drive Innovation -Be bold and unconstrained in problem solving. Transform the industry.
  • Embrace Learning -Engage our community to broaden our perspective. Bring a growth mindset.

In addition to our core values, Addepar is proud to be an equal opportunity employer. We seek to bring together diverse ideas, experiences, skill sets, perspectives, backgrounds and identities to drive innovative solutions. We commit to promoting a welcoming environment where inclusion and belonging are held as a shared responsibility.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Apply for this job#J-18808-Ljbffr

Related Jobs

View all jobs

Staff Software Engineer

Sr Staff Software Engineer

Architect / Staff Back-End Engineer, Trading Platform London

Staff Data Engineer and Team Lead

Senior Software Engineer, MLOps and Infrastructure

Staff Machine Learning Infrastructure Engineer, Simulation

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.