Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Asset & Wealth Management - Data Engineer - Associate - Birmingham

WeAreTechWomen
Birmingham
1 day ago
Create job alert
MORE ABOUT THIS JOB

Please note division and function examples are representative of opportunities common for this skill‑set. The list is not exhaustive, and availability of open roles is determined based on business need. Specific roles will be confirmed through the interview process.


Marcus by Goldman Sachs

The firm’s direct‑to‑consumer business, Marcus by Goldman Sachs, combines the entrepreneurial spirit of a start‑up with more than 150 years of experience. Today, we serve millions of customers across multiple products, leveraging innovative design, data, engineering and other core capabilities to provide customers with powerful tools and products that are grounded in value, transparency and simplicity.


Your Impact

This person will be:



  • responsible for expanding and optimizing our cloud based data pipeline architecture
  • building robust data pipelines and reporting tools

Basic Qualifications

  • 3+ years of experience in data processing & software engineering and can build high‑quality, scalable data oriented products
  • Experience on distributed data technologies (e.g. Hadoop, MapReduce, Spark, EMR, etc..) for building efficient, large‑scale data pipelines
  • Strong Software Engineering experience with in-depth understanding of Python
  • Strong understanding of data architecture, modeling and infrastructure
  • Experience with building workflows (ETL pipelines)
  • Experience with SQL and optimizing queries
  • Problem solver with attention to detail who can see complex problems in the data space through end to end
  • Willingness to work in a fast paced environment
  • MS/BS in Computer Science or relevant industry experience

Preferred Qualifications

  • Experience building scalable applications on the Cloud (Amazon AWS, Google Cloud, etc..)
  • Experience building stream‑processing applications (Spark streaming, Apache‑Flink, Kafka, etc..)

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.


We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.


We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html


© The Goldman Sachs Group, Inc., 2023. All rights reserved.


Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.


#J-18808-Ljbffr

Related Jobs

View all jobs

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice Pre[...]

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice Pre[...]

Asset & Wealth Management - Data Engineer - Associate - Birmingham Birmingham · United Kingdom [...]

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice Pre[...]

Data Scientist, Quantitative Strategies (Asset & Wealth Management)

Data Engineer III- Python & AWS

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.