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For Companies At a Glance
- Tasks: Lead data migration projects and architect cutting-edge data platforms using GCP tools.
- Company: Join a forward-thinking tech company in London, driving innovation in cloud data solutions.
- Benefits: Enjoy flexible working options, competitive pay, and opportunities for professional growth.
- Why this job: Be at the forefront of cloud technology, mentoring teams and shaping data strategies across industries.
- Qualifications: 12+ years in data architecture with expertise in Google Cloud services and strong programming skills required.
- Other info: Ideal for seasoned professionals looking to make a significant impact in a dynamic environment.
The predicted salary is between 72000 - 108000 £ per year.
Role: Cloud Data Architect
Location: London, UK
Duration: Contract
Key Responsibilities
- Provide technical leadership and strategic direction for enterprise-scale data migration and modernization initiatives.
- Architect end-to-end data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation.
- Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services).
- Drive data quality, governance, lineage, and security standards across enterprise data pipelines.
- Mentor engineering teams and lead best practice adoption across data architecture, orchestration, and DevOps tooling.
- Participate in technical workshops, executive briefings, and architecture reviews to evangelize GCP data capabilities.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field.
- 12+ years of experience in data architecture and data engineering with proven skills and leadership in large-scale cloud data programs.
- 5+ years of advanced expertise in Google Cloud data services: Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable.
- Hands-on experience with orchestration tools like Apache Airflow or Cloud Composer.
- Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow).
- Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some cases.
- Deep understanding of data lakehouse design, event-driven architecture, and hybrid cloud data strategies.
- Strong proficiency in SQL and experience with schema design and query optimization for large datasets.
- Expertise in BigQuery, including advanced SQL, partitioning, clustering, and performance tuning.
- Experience with version control systems (e.g., Git).
- Track record of success advising C-level executives and aligning technical solutions with business goals.
- Google Professional Data Engineer certification.
- Google Professional Cloud Architect certification or equivalent.
Preferred Qualifications
- Experience with modernization of on-premise and mainframe data environments into cloud-native architectures.
- Knowledge of regulatory data requirements across financial, healthcare, and telecom sectors.
- Familiarity with IaC (Terraform), GitOps, and CI/CD for data pipeline deployment.
- Strong communication, stakeholder management, and mentoring skills.
Contact Detail:
Infoplus Technologies UK Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GCP Cloud Architect
✨Tip Number 1
Network with professionals in the GCP community. Attend meetups, webinars, or conferences focused on Google Cloud technologies. Engaging with others in the field can lead to valuable connections and insights that may help you land the role.
✨Tip Number 2
Showcase your hands-on experience with GCP data services by contributing to open-source projects or creating your own projects. This practical demonstration of your skills can set you apart from other candidates.
✨Tip Number 3
Prepare for technical interviews by practising common GCP-related scenarios and problems. Familiarise yourself with case studies that involve data architecture and cloud migration, as these are likely to come up during discussions.
✨Tip Number 4
Research StudySmarter's current projects and initiatives related to cloud data architecture. Understanding our goals and challenges will allow you to tailor your conversations and demonstrate how you can add value to our team.
We think you need these skills to ace GCP Cloud Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Google Cloud data services and relevant technologies. Emphasise your leadership roles in data architecture and engineering, as well as any specific projects that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about cloud data architecture and how your skills can benefit the company. Mention your experience with data migration and modernization initiatives, and how you can act as a trusted advisor to stakeholders.
Showcase Relevant Projects: Include specific examples of projects where you have implemented end-to-end data platforms or defined processing pipelines. Highlight your hands-on experience with tools like Apache Airflow, Dataflow, and BigQuery, and how these contributed to project success.
Highlight Certifications: Clearly list your Google Professional Data Engineer and Cloud Architect certifications. If you have additional relevant certifications or training, make sure to include those as well, as they demonstrate your commitment to professional development in this field.
How to prepare for a job interview at Infoplus Technologies UK Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with GCP data services like Dataproc, Dataflow, and BigQuery. Highlight specific projects where you've architected data platforms or implemented complex data pipelines, as this will demonstrate your capability to lead enterprise-scale initiatives.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. For instance, you might be asked how you would approach a data migration project or handle data quality issues. Use the STAR method (Situation, Task, Action, Result) to structure your responses effectively.
✨Emphasise Leadership and Mentoring Skills
Since the role involves mentoring engineering teams, be ready to share examples of how you've led teams in adopting best practices in data architecture and DevOps tooling. Discuss your approach to fostering collaboration and knowledge sharing among team members.
✨Align Technical Solutions with Business Goals
Demonstrate your ability to act as a trusted advisor to senior stakeholders by discussing how you've previously aligned technical solutions with business objectives. Prepare to talk about your experience advising C-level executives and how you ensure that data strategies support overall business success.
