At a Glance
- Tasks: Design and optimise enterprise-grade data solutions for a leading commodities trader.
- Company: Join a major player in the commodities trading sector with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with a chance to work in a flat organisational structure.
- Why this job: Be the technical authority shaping impactful data architecture on a global scale.
- Qualifications: Deep experience in data architecture and hands-on expertise in data modelling required.
The predicted salary is between 36000 - 60000 £ per year.
As an Enterprise Data Architect for a major commodities trader, you will be the architectural 'backbone' and technical authority for a market-leading portfolio of data/analytics products. This is very much a hands-on architect role: you will design enterprise-grade data solutions and guide their delivery and impact globally, working with stakeholders ranging from engineering leads to energy traders.
Key responsibilities include:
- Defining the end-to-end data architecture across the enterprise, covering ingestion, storage, transformation, serving, and consumption layers.
- On-premise placement for data and analytics workloads, with explicit rationale and trade-off analysis.
- Designing and optimising data warehouses and data models (relational, dimensional, and where appropriate, vault or lake-house patterns).
- Evaluating and recommending BI technologies (e.g. Power BI, Tableau, Qlik, in-house charting) on a use-case basis, defining when each is appropriate and when it is not.
- Acting as a senior technical SME through the full project lifecycle: from discovery and design through to build, test, and production handover.
- Providing hands-on technical guidance during implementations: writing proof-of-concept code, troubleshooting issues, and unblocking delivery teams.
- Advising delivery teams on data architecture implications of design decisions, including feasibility, cost, performance, and maintainability.
Required qualifications and experience:
- Deep, demonstrable experience defining, developing, and evolving data architectures in complex, multi-domain organisations.
- Proven hands-on expertise in relational and dimensional data modelling, with the ability to justify modelling choices and explain trade-offs to others.
- Experience designing for both batch and real-time/streaming data patterns.
- Understanding of data mesh, data fabric, data warehouse, and lake-house concepts and when they do (and don’t) apply.
- Working knowledge of SQL at an advanced level; comfortable writing, reviewing, and optimising complex queries and DDL.
- Practical experience with at least one major cloud data platform (Azure Synapse/Fabric, Snowflake, Databricks, BigQuery, AWS Redshift) including cost and performance tuning.
- Experience in energy trading, commodities, or financial services data environments.
- Familiarity with data governance tooling.
- BSc in Computer Science, Information Management, or related discipline (or equivalent practical experience) from a Russell Group university.
- Experience with DataOps or MLOps practices and how they intersect with data architecture.
- Prior experience working in a flat or lean organisational structure where the architect is also involved with the implementation.
Enterprise Data Architect in London employer: Options Group
Options Group is an excellent employer, offering a vibrant work culture that fosters collaboration and innovation within the private markets investment team in Greater London. Employees benefit from comprehensive learning and development opportunities, competitive compensation, and the chance to work on impactful projects in private equity secondaries and co-investments, making it a rewarding environment for aspiring finance professionals.
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We think this is how you could land Enterprise Data Architect in London
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We think you need these skills to ace Enterprise Data Architect in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Options Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Options Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Options Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
