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

Apply Now

Vice President, Senior Data Engineer

BNY
City of London
1 week ago
Create job alert
Overview

Senior Data Engineer, Vice President — London. At BNY, our culture supports growth and success as a leading global financial services company. We work with clients to deliver transformative solutions using AI and advanced technologies, and we’re seeking a future team member to join the Investment Management Engineering team.

Responsibilities
  • Lead the design and development of data pipelines feeding the BNY Investments analytical platform, ensuring high quality and performance.
  • Provide architectural oversight by designing scalable, secure, and cost-efficient data systems tailored to BNY’s Investments business needs.
  • Contribute to the design and development of AI/ML initiatives ongoing in BNY Investments.
  • Mentor and coach junior and transitioning data engineers to accelerate their development and strengthen the team’s capabilities.
  • Lead production operations by enforcing standards around testing, CI/CD, observability, and documentation to ensure platform reliability and regulatory compliance.
  • Collaborate effectively with business clients and cross-functional teams to translate requirements into technical solutions and drive innovation across BNY.
Qualifications
  • Strong experience with Snowflake Data Cloud, including SQL, DBT and Snowpark.
  • Deep knowledge of Python, with experience building production-quality data pipelines and analytical jobs.
  • Expertise in data warehouse and modeling concepts for designing efficient database structures.
  • Familiarity with ML/AI concepts, models, and tools; experience using AI in a production capacity would be highly desirable.
About BNY and Awards

BNY is recognized as a top destination for innovators and champions of inclusion. We’re committed to equality and opportunity for all employees.

BNY Newsroom
BNY LinkedIn

Here’s a Few Of Our Recent Awards

  • America’s Most Innovative Companies, Fortune, 2025
  • World’s Most Admired Companies, Fortune 2025
  • “Most Just Companies”, Just Capital and CNBC, 2025
Our Benefits And Rewards

BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time.

BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.


#J-18808-Ljbffr

Related Jobs

View all jobs

Vice President, Senior Data Engineer

LLM / NLP Data Scientist Lead - Vice President - ESG

LLM / NLP Data Scientist Lead - Vice President - ESG

Data Engineer - Snowflake

Data Engineer - Snowflake

Director of AI Optimization and Productization - R&D Data Science & Digital Health

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.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.