At a Glance
- Tasks: Lead data architecture initiatives and establish standards for effective data use.
- Company: Join a forward-thinking organisation focused on data-driven decision making.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Shape the future of data architecture and influence key organisational decisions.
- Qualifications: Experience in data modelling and architecture, with strong communication skills.
The predicted salary is between 72000 - 88000 £ per year.
About the role: The role is to provide leadership for the data architecture, establishing data models, standards and design principles that enable trusted, connected and effective use of data to support organisational priorities and informed decision making.
You will: Act as the authority for Data Architecture, providing specialist expertise, thought leadership, and guidance on data design, modelling, and data architecture standards.
Define, maintain, and evolve the data architecture, ensuring alignment with organisational priorities, data strategy and future business needs.
Lead the development and maintenance of enterprise, domain, conceptual, logical and physical data models, creating a shared understanding of data across the business.
Establish and maintain data architecture principles, standards, reference architectures and design patterns that support trusted, scalable, and sustainable use of data.
Lead data architecture governance and design assurance, providing challenge, recommendations and architectural oversight for significant data initiatives and programmes.
Provide expert advice to senior stakeholders, influencing decisions through evidence-based recommendations and helping teams understand architectural options, risks and trade-offs.
Build consensus across teams and programmes, ensuring data architecture standards and principles are consistently applied across platforms, solutions and services.
Define architecture approaches that improve interoperability, integration, governance, and reuse of data, supporting more efficient and joined-up services across the business.
Identify and manage data architecture related risks, technical debt and opportunities, ensuring emerging issues are addressed and escalated appropriately.
Promote data architecture capability and maturity by coaching, mentoring and supporting colleagues, fostering greater understanding and adoption of good architecture practices.
Significant experience defining, implementing and evolving data architectures that support organisational strategy, transformation, and business outcomes.
Demonstrable expertise in conceptual, logical and physical data modelling, including the development of enterprise and domain level data models.
Experience establishing architecture principles, standards, governance processes and design assurance that support consistent and effective decision making.
Strong understanding of data management and governance practises, including metadata, lineage, reference, master data, stewardship, with the ability to embed these principals into data architecture design.
Experience designing data architecture for modern cloud-based data platforms, data integration patterns, preferably with Microsoft Azure ecosystem and Microsoft Fabric.
Experience aligning data architecture decisions with organisational strategy, ensuring data models, standards and approaches support current priorities and future transformation.
Proven ability to influence decisions, build consensus, and secure adoption of standards across teams without direct reporting authority.
Ability to communicate complex technical concepts, risks, options and recommendations clearly to technical and non-technical audiences, including senior stakeholders.
Ability to provide technical leadership through expertise, coaching and collaboration, supporting adoption of good data practise.
Demonstrable ability to analyse complex issues, evaluate options and make evidence-based recommendations in situations where risk, ambiguity or limited precedent exists.
Experience working within education, skills, public sector or other complex data environments involving data sharing, multiple stakeholders and evidence-based decision making.
Experience with Microsoft Fabric, Azure Data Factory, Databricks, Power BI semantic models or equivalent technologies.
Professional qualification or certification in Data Architecture, Enterprise Architecture, Data management, or Data Engineering (e. g.
TOGAF, DAMA CDMP, MS Azure Solutions Architect, MS Fabric Data Engineer) #J-18808-Ljbffr
Data Architect in Essex employer: Harvey Nash
Join a dynamic global banking organisation that prioritises innovation and employee development. With a collaborative work culture, comprehensive benefits, and ample opportunities for professional growth, this role as a SWIFT / Payments Project Manager offers a chance to make a significant impact in the financial sector while enjoying a supportive environment in a thriving location.
StudySmarter Expert Advice🤫
We think this is how you could land Data Architect in Essex
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Harvey Nash!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Architect at Harvey Nash.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Harvey Nash.
✨Apply Directly through Our Website
When you find a suitable opening like Data Architect at Harvey Nash, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Architect in Essex
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Harvey Nash, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Harvey Nash. 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 Harvey Nash
✨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!
✨Showcase Your Projects
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 Harvey Nash!
✨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.
