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- Tasks: Design and build scalable data pipelines while managing analytical workflows.
- Company: Leading analytics firm in Greater London with a focus on innovation.
- Benefits: Enjoy 40 days of holiday and comprehensive health insurance.
- Why this job: Join a dynamic team and contribute to impactful data-driven decisions.
- Qualifications: Proficient in Python and SQL, with experience in data modelling and ML ops.
- Other info: Work with modern tools like dbt and BigQuery in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading analytics firm in Greater London is seeking an Analytics Engineer to design and build scalable data pipelines and manage analytical workflows. This role requires strong proficiency in Python and SQL, along with experience in data modelling and machine learning operations. You will work with modern data tools like dbt and BigQuery, contributing to a robust analytics environment that supports data-driven decision-making.
Benefits include 40 days of holiday and comprehensive health insurance.
Analytics Engineer: Build Scalable Data Pipelines & ML Ops employer: Exinity
Contact Detail:
Exinity Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer: Build Scalable Data Pipelines & ML Ops
✨Tip Number 1
Network like a pro! Reach out to folks in the analytics space, especially those who work with data pipelines and ML Ops. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and SQL. We all love a good visual, so include some cool data models or machine learning workflows you've built.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of dbt and BigQuery. We want you to feel confident discussing how you can contribute to a robust analytics environment.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Analytics Engineer: Build Scalable Data Pipelines & ML Ops
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your proficiency in Python and SQL right from the get-go. We want to see how you can design and build those scalable data pipelines, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Take a moment to customise your application for this role. Mention your experience with data modelling and ML Ops, and how you've used tools like dbt and BigQuery in past projects. This helps us see how you fit into our analytics environment.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Avoid fluff – we want to know what you can bring to the table!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Exinity
✨Know Your Tech Stack
Make sure you’re well-versed in Python and SQL, as these are crucial for the role. Brush up on your knowledge of dbt and BigQuery too, as being able to discuss how you've used these tools in past projects will impress the interviewers.
✨Showcase Your Data Modelling Skills
Prepare to talk about your experience with data modelling. Have specific examples ready that demonstrate how you've designed effective data models and the impact they had on previous projects. This will show your practical understanding of the role.
✨Discuss Machine Learning Operations
Since the role involves ML Ops, be ready to discuss your experience in this area. Talk about any machine learning projects you've worked on, the challenges you faced, and how you overcame them. This will highlight your problem-solving skills and technical expertise.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s analytics environment and how they leverage data for decision-making. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
