Azure Data Engineer — Hybrid, Client‑Facing Projects

DATA ENGINEER – CONSULTANCY EXPERIENCE

• Salary up to £90,000 + discretionary bonus
• London-based role with hybrid working
• Work across high-impact client projects
• Broad exposure to modern Azure data stack and cloud technologies
• Strong progression and training opportunities within a growing consultancy

Due to continued growth, we’re supporting a well‑established consultancy specialising in data strategy and technology solutions within the financial services space. They work closely with a global client base, delivering high‑quality, hands‑on solutions rather than purely advisory services.

• Competitive salary with discretionary bonus
• Hybrid working model
• Private healthcare
• Enhanced pension contributions
• 25 days holiday, increasing with tenure
• Ongoing training and career development
• Exposure to a wide range of technologies and clients

You’ll play a key role in delivering end‑to‑end data solutions, working closely with clients to design, build, and implement scalable data platforms. This is a hands‑on, client‑facing role where you’ll contribute to solution design, gather requirements, and support project delivery from concept through to completion.

You’ll also collaborate with project managers on complex engagements, provide technical insight into proposals and Statements of Work, and support governance and best practice across projects. There’s a strong focus on innovation, with opportunities to contribute ideas and shape how solutions are delivered.

• Strong experience in data engineering and building scalable data solutions
• Solid understanding of data architecture and design patterns
• Experience with cloud platforms, particularly Azure
• Data warehousing experience (e.g. Snowflake, Azure SQL)
• Strong SQL and data modelling skills
• Experience with ETL/ELT pipelines and modern data tooling
• Ability to engage with stakeholders and communicate technical concepts clearly
• Experience contributing to project planning, scoping, and delivery

Data Engineering, SQL, Python, Azure, Snowflake, ETL, Data Warehousing, Data Architecture, Data Pipelines, CI/CD