Principal Google Cloud Architect

• Project Leadership: Oversee the design and implementation of enterprise-scale Data and AI projects.
• Technical Thought Leadership: Introduce innovative ideas and approaches to enhance Datatonic's capabilities and methodologies.
• Team and Architecture Development: Shape the architecture team and mentor team members while promoting technical excellence.
• Sales Support: Collaborate with sales teams to provide technical expertise during client engagements and help scope solutions for challenging requirements.
• Solution Development: Partner with GTM teams to create and refine new market-ready solutions with a focus on technical leadership and governance.
• Customer Engagement: Conduct architecture reviews for key clients, delivering actionable recommendations to senior stakeholders.
• Technical Best Practices: Define and embed best practices into project delivery, ensuring quality and consistency across initiatives.
• Knowledge Sharing: Contribute to Datatonic's internal knowledge base, including technical collateral and thought leadership materials.
• Agile Collaboration: Work in a dynamic, agile environment alongside data scientists, machine learning experts, data analysts, and data engineers.
• Tech Partner Collaboration: Collaborate closely with partners such as Google Cloud, Tableau, and Looker to leverage their technologies effectively.
• Mentorship and Leadership: Guide team members, fostering a culture of growth and innovation.

This is an excellent opportunity for an experienced professional in cloud technologies who would like to work as part of a team of experts in the fields of AI and data, as a subject matter expert in solution/cloud architecture. The role is customer-facing, working closely with business and technical influencers, and will require a background in Computer Science.

Successful candidates will bring multiple years' experience with cloud platforms like Google Cloud or AWS. Ideally, you'll have served as an SME in designing and migrating applications to live in the cloud, working with complex cloud deployments, and being adept at the design and implementation of complex platforms., * Educational Background: Bachelor's or Master's degree in Computer Science or a related technical discipline.

• Proven Expertise: Hands-on experience in designing and implementing large-scale big data cloud architectures.
• End-to-End Ownership: Demonstrated ability to manage projects from conception to completion, employing creative and practical solutions.
• Technical Prowess: Strong analytical skills with a focus on innovation and technical excellence.
• Effective Communication: Exceptional verbal and written communication skills, with an eye for detail and the ability to deliver authoritative presentations and proposals.
• Stakeholder Management: Skills in developing and maintaining relationships with key external stakeholders at various organizational levels.
• Pre-Sales Experience: Extensive experience in technical pre-sales, with the ability to champion and promote innovative, disruptive proposals.
• Holistic Cloud Expertise: Comprehensive knowledge of end-to-end production-grade cloud technologies, covering areas such as data, security, and networking.
• Container Technology Experience: Proficiency in working with container technologies and leveraging them effectively in projects.
• Programming Proficiency: Multiple years of experience in programming languages such as Python, Java, and SQL, with a focus on building scalable, high-performance code.
• Solution Delivery: Demonstrated experience in delivering scalable, robust, and high-performing solutions to meet business needs.

Bonus Points If You Have:

• Certifications: Google Cloud or AWS Certified Solutions Architect certification.
• ETL and Data Pipeline Expertise: Experience with ETL tools and Hadoop-based technologies (e.g., Spark) and/or batch/streaming data pipelines such as Beam and Flink.
• Data Architecture: Proven ability in designing and building data lake and data warehouse solutions with technologies like BigQuery, Azure Synapse, Redshift, Oracle, Teradata, etc.
• Analytics Tools: Experience creating analytical products using tools such as Looker, Tableau, Data Studio, PowerBI, or Qlik.
• Agile Methodologies: Familiarity with Agile frameworks, including Scrum.
• Data Science Knowledge: Basic understanding of topics like machine learning, data mining, statistics, and data visualisation, with some practical experience preferred.
• Open-Source Contributions: History of contributions to open-source projects, showcasing collaboration and innovation.

Pulled from the full job description

• Life insurance
• Company pension
• Private medical insurance
• Cycle to work scheme
• Tech scheme
• Discounted gym membership

Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn't just encouraged - it's embedded in everything we do. If you're ready to inspire change and deliver value at the forefront of data and AI, we'd love to hear from you!