Staff Data Engineer London / Remote

Sotheby’s group
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Staff Data Engineer

Senior Data Engineer (AWS, Airflow, Python)

Staff Data Engineer

Staff Data Engineer

Data Engineer (18 Months FTC)

Data Engineer (18 Months FTC)

Established in 1744, Sotheby’s is the world’s premier destination for art and luxury. Sotheby’s promotes access to and ownership of exceptional art and luxury objects through auctions and buy-now channels including private sales, e-commerce and retail. Our trusted global marketplace is supported by an industry-leading technology platform and a network of specialists spanning 40 countries and 70 categories which include Contemporary Art, Modern and Impressionist Art, Old Masters, Chinese Works of Art, Jewelry, Watches, Wine and Spirits, and Design, as well as collectible cars and real estate. Sotheby’s believes in the transformative power of art and culture and is committed to making our industries more inclusive, sustainable and collaborative.

THE ROLE

Sotheby's Data Team is empowering the organization using deep insights that matter. We are seeking a talented and motivated leader to accelerate our efforts to drive trust, adoption, and democratization of insights. This role will work closely with Engineering, Product, Operations, and Research teams to build systems of intelligence empowering product development while uncovering business opportunities from data. A successful candidate will be both technically strong and business savvy while being able to provide great leadership and mentorship to this team and champion & adopt scalable workflows while streamlining processes.

RESPONSIBILITIES

  • Define the technical data architecture and strategy for our Data Engineering and Business Intelligence teams.
  • Working hands on, side by side with other data engineers to implement robust solutions
  • Design, develop, and deploy data warehouse solutions that support the objectives of internal stakeholders.
  • Create blueprints for data management systems to integrate, protect, and maintain data systems by understanding intricacies of Sotheby’s data.
  • Drive initiatives focused on data preparation, integration, and exploration.
  • Develop and Implement Data governance best practices and data security policies.
  • Architect data ingestion pipelines including monitoring and quality tests
  • Design and implement analytics solutions that enable consistency & scalability with cross-functional teams.
  • Own business metrics for the business, while monitoring changes in KPIs that impact business performance
  • Define, prioritize, deliver and communicate metrics & analyses across the business, including senior executives

IDEAL EXPERIENCE & COMPETENCIES

  • Degree in business, computer science, statistics, applied mathematics or other quantitative field
  • 6+ years of experience as a data Engineer
  • Deep knowledge of data models, experimental design, and execution
  • Understanding of Snowflake architecture, cost management, and optimization
  • Software experience, specifically APIs, development cycle, integrations
  • Expertise with python, SQL, HTML
  • Experience leading complex technical projects with engineer partners (engineers and data engineers)
  • Experience with AWS tools, specifically RDS, Lambdas, s3
  • Practical experience with Data Warehouse technologies specifically Snowflake, dbt, and Fivetran
  • Snowflake Infrastructure expertise with role management, Snowpark admin, Streamlit, etc
  • Strong experience with Tableau administration and ERP systems (SAP)
  • Strong ability to communicate complicated and nuanced insights in accessible language to relevant stakeholders

To view our Candidate Privacy Notice for the US, please click here .

To view our Candidate Privacy Notice for the UK, Hong Kong, France and Switzerland, please click here .

The Company is an equal opportunity employer and considers all applicants for employment without regard to race (including, without limitation, traits historically associated with race, such as natural hair, hair texture, and protective and treated or untreated hairstyles), color, creed, religion, sex, sexual orientation, marital or civil partnership/union status, national origin, age, disability, pregnancy, genetic predisposition, genetic information, reproductive health decision, sexual orientation, gender identity or expression, alienage or citizenship status, domestic violence victim status, military or veteran status, or any other characteristic protected by federal, state/province or local law. The Company complies with applicable state and local laws prohibiting discrimination in employment in every jurisdiction in which it operates.

Create a Job Alert

Interested in building your career at Sotheby's? Get future opportunities sent straight to your email.

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Have you previously worked/do you currently work for Sotheby's? *

I am a current Sotheby’s employee

I am currently in Sotheby's Associates Program

I am a former Sotheby’s employee

I have never been employed by Sotheby's

If yes, please provide estimated dates you were employed

How did you hear about this opportunity? *

If you heard about this opportunity from a Sotheby's employee, who referred you?

Are you authorized to work in the country in which this job is offered? * Select...

Will you now or in the future require Sotheby's sponsorship to continue or extend your current work authorization status? * Select...

What is your desired salary? *

What is your notice period? *

LinkedIn Profile

How many professional years of experience do you have using Snowflake? *

How many professional years of experience do you have using AWS? *


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.