At a Glance
- Tasks: Build robust data pipelines on GCP and collaborate with data scientists.
- Company: Ipsos, a leader in audience measurement and data solutions.
- Benefits: Competitive salary, cloud-native environment, and cross-training opportunities.
- Other info: Hybrid work setting in London with excellent career growth.
- Why this job: Join a dynamic team and make an impact in data engineering.
- Qualifications: Experience in Python, ETL, and CI/CD practices.
The predicted salary is between 50000 - 70000 £ per year.
Ipsos is recruiting a Data Engineer to help evolve our Audience Measurement data platforms.
You will work with a team to build robust data pipelines on GCP, using Python for backend processing, and apply serverless and Ia C practices.
The role involves collaborating with data scientists, implementing ETL and CI/CD, and contributing to data contracts and Data Ops within a hybrid London-based setting.
Join a cloud-native environment on AWS/GCP, with cross-training opportunities and a focus on
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Hybrid Data Engineer: Cloud Pipelines on GCP employer: Ipsos
Ipsos is an excellent employer that values its employees by providing a supportive work culture and opportunities for professional growth. Based in Dartford, Kent, our team enjoys a collaborative environment where every voice is heard, and we offer competitive salaries along with comprehensive benefits to ensure a rewarding career in market research.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Data Engineer: Cloud Pipelines on GCP
✨Get Involved in Data Science Meetups
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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 Ipsos.
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We think you need these skills to ace Hybrid Data Engineer: Cloud Pipelines on GCP
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 Ipsos, 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 Ipsos. 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 Ipsos
✨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 Ipsos!
✨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.
