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
2 months ago
Applications closed

Related Jobs

View all jobs

Asset & Wealth Management - Equities Quantitative Investment Analyst - Associate/ Vice President

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

Vice President, Data Architect

Alpha Enviroment and Data Strategy Manager, Vice President

Commercial Investment Bank - Lead Data Architect - Associate or Vice President

VP, AI/ML Platform & Data Governance

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

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

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.