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- Tasks: Design and implement scalable data architecture on Azure, ensuring data integrity and security.
- Company: Join a global investment firm leading a major data transformation initiative.
- Benefits: Enjoy hybrid working, career development opportunities, and a supportive team culture.
- Why this job: Be at the forefront of modernising data systems with cutting-edge technologies like Databricks and Python.
- Qualifications: Strong background in data architecture, preferably in financial services, with experience in Azure and data modelling.
- Other info: Collaborate with diverse teams to align technical solutions with business needs.
The predicted salary is between 43200 - 72000 £ per year.
A global Investment firm is embarking on a major enterprise-wide modernisation programme and requiring senior Data Architect to help shape the future of its data landscape. This high-priority initiative will see the organisation move from complex legacy systems to a modern, cloud-based environment, leveraging the power of Azure, Python, and Databricks.
You will be central to designing the data architecture that underpins this transformation, ensuring data is scalable, secure, and built for both operational agility and strategic insight.
- Design and implement robust, scalable data architecture on the Microsoft Azure cloud platform.
- Define data standards, domains, and governance frameworks to support business-critical functions like trading, risk, operations, and regulatory reporting.
- Build both real-time and batch data pipelines to support fast, data-driven decision-making.
- Model enterprise data structures and ensure alignment across systems and teams.
- Collaborate closely with Data Engineers, Software Developers, and Business Stakeholders to align technical solutions with commercial needs.
- Establish clear data quality metrics and processes to enforce data integrity and security.
Strong background as a Data Architect, ideally within financial services or commodities trading. Proven experience with Azure, Databricks, and enterprise data lake solutions. Hands-on experience with data modelling, ETL/ELT pipelines, and data integration across multiple systems. Experience with relational databases such as Oracle and SQL Server. Knowledge of data governance platforms like Purview or Collibra is a plus.
Be at the heart of a high-impact data transformation programme. Work with cutting-edge technologies including Databricks, Python, and Azure. Join a supportive and inclusive team, offering hybrid working and strong career development.
Data Modeller - Hybrid Working employer: twentyAI
Contact Detail:
twentyAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeller - Hybrid Working
✨Tip Number 1
Familiarise yourself with the latest trends and technologies in data architecture, especially focusing on Azure, Databricks, and Python. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the financial services sector who are currently working as Data Architects. Attend industry meetups or webinars to gain insights and potentially get referrals that could boost your application.
✨Tip Number 3
Prepare to discuss specific projects where you've implemented data governance frameworks or built data pipelines. Real-world examples will demonstrate your hands-on experience and problem-solving skills, making you a more attractive candidate.
✨Tip Number 4
Showcase your collaborative skills by highlighting experiences where you've worked closely with Data Engineers, Software Developers, and Business Stakeholders. Emphasising teamwork can set you apart, as this role requires strong collaboration across various teams.
We think you need these skills to ace Data Modeller - Hybrid Working
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience as a Data Architect, particularly in financial services or commodities trading. Emphasise your hands-on experience with Azure, Databricks, and data modelling to align with the job requirements.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's modernisation programme. Discuss how your skills in designing scalable data architecture and building data pipelines can contribute to their transformation goals.
Showcase Technical Skills: Clearly outline your technical skills related to Azure, ETL/ELT processes, and data integration. Mention any experience with relational databases like Oracle and SQL Server, as well as knowledge of data governance platforms if applicable.
Highlight Collaboration Experience: Since the role involves working closely with Data Engineers, Software Developers, and Business Stakeholders, include examples of past collaborations that demonstrate your ability to align technical solutions with commercial needs.
How to prepare for a job interview at twentyAI
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Azure, Databricks, and data modelling in detail. Highlight specific projects where you've designed scalable data architectures or built data pipelines, as this will demonstrate your hands-on expertise.
✨Understand the Business Context
Familiarise yourself with the financial services sector and the specific challenges it faces regarding data management. This knowledge will help you align your technical solutions with the commercial needs of the organisation, showing that you can think strategically.
✨Emphasise Collaboration
Since the role involves working closely with Data Engineers, Software Developers, and Business Stakeholders, be ready to discuss your experience in collaborative environments. Share examples of how you've successfully worked in teams to achieve common goals.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in previous roles, particularly around data governance and integrity, and be ready to explain how you addressed them.
