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- Tasks: Lead the engineering team in building data solutions on GCP.
- Company: Join a forward-thinking tech company focused on innovative data solutions.
- Benefits: Enjoy flexible working options and exciting corporate perks.
- Why this job: Be part of a dynamic culture that values creativity and impact in data analytics.
- Qualifications: 12+ years IT experience, with strong GCP and Python skills required.
- Other info: Experience with Kubernetes is a plus; great communication skills are essential.
The predicted salary is between 72000 - 108000 £ per year.
Key Responsibilities:
- 12+ years of overall IT experience with 10+ years in building data warehouse/datamart solutions.
- Experience in implementing an end-to-end data platform for analytics on cloud from ingestion to datamart.
- 4+ years of experience in GCP services namely Dataflow, Big Query, GCS.
- 4+ years of experience in Python; 2+ years of experience in PySpark.
- Knowledge of GCP Kubernetes would be an advantage.
- Knowledge of data warehousing concepts with a good understanding of dimensional models.
- Experience in implementing a metadata framework for data ingestion, data quality, and ETL.
- Good communication skills and ability to manage IT stakeholders.
GCP Data Lead employer: N Consulting Limited
Contact Detail:
N Consulting Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GCP Data Lead
✨Tip Number 1
Make sure to showcase your extensive experience in building data warehouse solutions. Highlight specific projects where you've implemented end-to-end data platforms, especially on GCP, as this will resonate with our requirements.
✨Tip Number 2
Familiarise yourself with the latest GCP services, particularly Dataflow and BigQuery. Being able to discuss recent updates or features during an interview can demonstrate your commitment and expertise in the field.
✨Tip Number 3
Prepare to discuss your experience with Python and PySpark in detail. Be ready to provide examples of how you've used these technologies to solve complex data challenges, as practical knowledge is key for this role.
✨Tip Number 4
Brush up on your communication skills, as managing IT stakeholders is crucial for this position. Think of scenarios where you've successfully communicated technical concepts to non-technical audiences, as this will be valuable in our collaborative environment.
We think you need these skills to ace GCP Data Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data warehousing and GCP services. Emphasise your 12+ years of IT experience and detail your specific roles in building data platforms, especially focusing on the technologies mentioned in the job description.
Craft a Strong Cover Letter: In your cover letter, explain why you are a great fit for the GCP Data Lead position. Mention your experience with Dataflow, Big Query, and Python, and how these skills will contribute to the company's goals. Use specific examples from your past work to illustrate your points.
Highlight Key Skills: Ensure that your application clearly lists key skills such as data ingestion, ETL processes, and metadata frameworks. If you have experience with Kubernetes, make sure to mention it as an advantage, even if it's not your primary focus.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A well-written application reflects your attention to detail and professionalism, which is crucial for a leadership role.
How to prepare for a job interview at N Consulting Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with GCP services like Dataflow, BigQuery, and GCS. Highlight specific projects where you implemented these technologies, focusing on the challenges you faced and how you overcame them.
✨Demonstrate Your Leadership Skills
As a GCP Data Lead, you'll need to manage stakeholders effectively. Prepare examples of how you've led teams or projects in the past, showcasing your ability to communicate complex ideas clearly and motivate others.
✨Understand Data Warehousing Concepts
Brush up on your knowledge of data warehousing and dimensional models. Be ready to explain how you've applied these concepts in your previous roles, particularly in relation to building data warehouse solutions.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about potential data ingestion or ETL challenges and how you would address them using your technical expertise and experience.
