At a Glance
- Tasks: Design and implement cutting-edge data solutions using Google Cloud technologies.
- Company: Join Datatonic, a leading AI and data transformation partner for top businesses.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on mentorship and career development.
- Why this job: Make a real impact in the AI and data landscape while working with innovative technologies.
- Qualifications: Experience in data architecture, strong data modelling skills, and proficiency in SQL.
The predicted salary is between 72000 - 88000 £ per year.
Shape the Future of AI & Data with Us At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses.
We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud.
Your Mission As a Principal Data Architect, you will play a pivotal role in designing and implementing modern, scalable data solutions for our clients.
Working closely with colleagues across the Data & Analytics Engineering teams, you will help architect, build, and optimise new data platforms or migrate existing solutions to Google Cloud.
This is an exciting opportunity for a highly-experienced data professional who is passionate about leveraging cloud technologies to drive innovation and efficiency.
You will consult with our clients to understand their business needs and objectives, gather requirements, and define and deliver robust, high-performance data architectures.
If you thrive in a fast-paced, technology-driven, consulting environment and are eager to make a tangible impact on transformative projects, this role is for you.
What You’ll Do Design & Deliver Cutting-Edge Data Solutions - Lead the analysis, design, and execution of state-of-the-art, data-driven solutions to meet our client’s business needs, leveraging the best of Google Cloud technologies.
Data Architecture & Governance - Serve as an expert in data transformation, storage, retrieval, security, and governance, ensuring scalable, secure, and efficient data solutions.
Guide & Mentor Engineers - Provide architectural direction to engineers, ensuring they build robust, high-performance solutions aligned with your target data architecture.
Master Data Modeling Techniques - Apply expertise in various data modeling approaches, including 3NF, Data Vault, Star Schema, and One Big Table (OBT).
Clearly articulate the benefits and trade-offs of each method and optimize their implementation within columnar databases such as Big Query.
Shape Data Strategy - Collaborate with the client to define and refine data strategy, covering: Data governance and compliance Scalable and efficient data modeling techniques Ensuring data quality and integrity Data management, security, and privacy best practices Establishing optimal workflows and operational efficiencies Develop Fully Integrated Solutions - Work alongside Architecture, Engineering, and Data Science teams to design comprehensive, production-ready solutions that incorporate: Google Cloud - Big Query, Dataflow, Vertex AI, and moredbt Labs - Modern analytics engineering and transformation Snowflake - Cloud-native data warehousing Fivetran - Automated data pipelines for seamless integration What You’ll Bring Data Architecture - Proven experience designing and building data warehouse / lakehouse solutions using technologies like Big Query, Azure Synapse, Snowflake, Databricks Data Modeling - Strong expertise in data modeling and solution architecture, optimizing for performance and scalability Data Governance - Experience with data platforms with data quality, security, privacy, and governance controls built-in Ownership Mindset - Ability to take projects from concept to completion, driving creative and effective solutions Analytical & Technical Excellence - Demonstrated problem-solving skills with a strong technical foundation and an innovative approach Communication & Presentation - Exceptional written and verbal communication skills with great attention to detail, capable of presenting complex concepts clearly to customers Stakeholder Management - Ability to build and maintain strong relationships with key external stakeholders across different business levels Programming Proficiency - Hands-on experience with Python, Java, and SQL for data engineering and solution development Why Datatonic?Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow.
If you’re ready to inspire change and deliver value at the forefront of data and AI, we’d love to hear from you!
Data Architect - SQL in London employer: Datatonic
Datatonic is an exceptional employer that prioritises a culture of continuous learning and innovation, making it an ideal place for the Head of Learning & Development role. With a strong focus on employee growth, you will have the opportunity to shape global learning strategies while collaborating with top-tier talent in a vibrant environment. Located in London, you will benefit from being part of a fast-growing, award-winning consultancy that values your contributions and fosters a supportive community.
StudySmarter Expert Advice🤫
We think this is how you could land Data Architect - SQL in London
✨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 Datatonic!
✨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 - SQL at Datatonic.
✨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 Datatonic.
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When you find a suitable opening like Data Architect - SQL at Datatonic, 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 - SQL 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!
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 Datatonic, 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 Datatonic. 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 Datatonic
✨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 Datatonic!
✨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.
