Data Engineer (Python) -TOP Asset Manager!

Robert Half
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data engineer

Data Engineer


Data Engineer (Python) -TOP Asset Manager!

Do you want to work in a brand-new team with full Autonomy?

Are you driven and commercial? Do you like working in a fast-paced environment?

Do you want to work in a company where you can make a BIG Impact?

The Data Engineer must come from some of Fintech, Financial services, Insurance, PE/VC fund or Banking background.

This role is based in London -3days onsite and 2 days from home. More flexibility when and if needed. You will be working with a Pragmatic Hiring Manager who has a good understanding of emotional intelligence.

Vision for this role:

The Data Engineer will be joining a BRAND-NEW Team and play a pivotal role in the current and future data strategy. You will be working with a High-End Technology Tech Stack which allows a Robust Data Pipeline for Data Lake Infrastructure that allows Portfolio managers to collect, validate and analyse large datasets.

Qualifications/experience required

Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field 2+ years experience in business analytics, data science, software development, data modelling or data engineering work, ideally in Tech or Financial Services/FinTech 1+ years experience as a Data Engineer manipulating and transforming data in Spark SQL, PySpark, or Spark Scala 1+ years experience manipulating and transforming data in TSQL 1+ years experience translating business requirements to technical requirement. Proficiency in Python, Microsoft Power Apps, GA, Big Query and Power BI highly recommended

Competencies/skill set

Proficiency in programming languages such as Python and SQL for data processing, manipulation, and analysis Experience with big data technologies and frameworks. Proficiency in Apache Spark and experience with Spark SQL,

PySpark for distributed data processing and storage

Strong understanding of data modelling concepts, ETL and ELT processes, and data warehousing principles Knowledge of cloud computing platforms, in particular Azure, and experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, and Azure Databricks for data storage, processing, and analytics Knowledge and experience with Git operations, GitHub copilot and CI/CD flows Familiarity with data visualisation tools and techniques, especially Power BI, for creating interactive dashboards and reports Passion for data and the desire to learn & adopt new technologies

đź’°This role offers a competitive base salary and up to 10-20% bonus potential,

25 days holidays

Pension

Medical Care
📝 Don't miss out on this opportunity to work with one of the best in the industry!

If you're interested in this opportunity, submit your CV as soon as possible. Interviews will be arranged ASAP!

Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to equal opportunity and diversity. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training.

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.