Data Architect

Data Engineer / Data ArchitectLocation: London / Hybrid
Salary: Dependent on experience
Type: Permanent, with potential for an initial contract architecture engagement
I'm working with a growing wealth management business looking to strengthen its data platform and bring greater consistency, accuracy and reliability to the financial data flowing through its systems.
They're looking for a hands-on Data Engineer with strong architectural instincts who can take ownership of data quality, pipeline development and data modelling across multiple incoming sources. This isn't a traditional backend engineering role. The focus is on ensuring financial data is correctly structured, normalised, reconciled and ready to be used across the platform.
The ideal candidate will be comfortable working in a fast-paced environment, getting into the technical detail and challenging existing approaches to build a more robust and scalable data infrastructure.
The RoleYou'll work across the data platform, developing and optimising pipelines that bring together client and market data from multiple sources. A key part of the role will be ensuring that data is not only technically processed but also accurate and consistent from a financial perspective.
You'll have ownership of data logic, transformations and validation, with the opportunity to influence how the wider platform is structured. The business is particularly interested in someone who can combine hands-on engineering with a broader architectural mindset.
Key Responsibilities

• Design, develop and maintain data pipelines using Python, SQL, PostgreSQL and Snowflake.
• Integrate and transform data from multiple incoming sources, ensuring consistency, normalisation and reliability.
• Build robust data models and implement appropriate data structures across the platform.
• Develop reconciliation processes, validation rules and exception handling to identify discrepancies, duplicates, missing data and inconsistent identifiers.
• Establish data quality checks, lineage and monitoring to improve transparency and confidence in financial data.
• Optimise Snowflake performance, including query efficiency and parallel versus sequential processing.
• Work with APIs and external data sources to ensure reliable data ingestion and transformation.
• Apply Medallion Architecture principles to structure data effectively across ingestion, transformation and consumption layers.
• Take ownership of key pipelines and deliver visible improvements to data quality and reliability.
• Work closely with the wider team to sense-check technical decisions and help shape the future architecture of the platform.

What We're Looking For

• Strong hands-on experience with SQL and Python.
• Practical experience building data pipelines, transformations and integrations.
• Experience with Snowflake, including query optimisation and performance tuning. PostgreSQL or other relational database experience is also relevant.
• A solid understanding of data modelling, normalisation and data architecture principles.
• Experience implementing data validation, reconciliation, monitoring and exception-handling processes.
• Familiarity with Medallion Architecture or similar modern data platform frameworks.
• An understanding of how data quality issues can affect downstream business decisions, particularly in financial services.
• Ideally, experience within wealth management, investments or financial markets, with an understanding of instruments such as equities, bonds and dividends.
• A proactive, hands-on approach and the ability to operate in a growing business where priorities can change quickly.

The Ideal CandidateWe're interested in someone who sits between a traditional Data Engineer and a Data Architect. You should be comfortable writing code and building pipelines yourself, while also understanding how the underlying data structures, processing logic and controls need to fit together.
Experience within wealth management or investment data would be particularly valuable. You don't necessarily need to be a financial markets specialist, but an understanding of how investment data works and why accuracy matters is important.
You'll suit an environment where you can take ownership, make practical decisions and help build processes and infrastructure that can scale as the business grows.
Why Consider It?

• The opportunity to influence the architecture and quality of a growing financial data platform.
• A hands-on role combining engineering, data modelling and architectural thinking.
• The chance to work with investment and market data where accuracy and reconciliation are critical.
• An environment that values initiative, technical curiosity and the ability to get things done.

Interested? If you're a Data Engineer with strong Python, SQL and Snowflake experience, particularly within wealth management or investment data, I'd be keen to have a confidential conversation.

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