At a Glance
- Tasks: You'll model, transform, and wrangle data while tackling exciting challenges.
- Company: Join a fast-growing SaaS platform with a global presence in the UK, US, and Australia.
- Benefits: Enjoy a competitive salary, remote work options, and a dynamic team environment.
- Other info: The role includes a three-stage interview process and offers a collaborative culture.
- Why this job: Be part of a successful data team and make an impact in a thriving industry.
- Qualifications: Experience in SQL, Python, and cloud platforms is essential; strong problem-solving skills are a must.
The predicted salary is between 48000 - 72000 £ per year.
Cognify have partnered with a fast-growing SaaS platform as they continue to expand their data team following a consistent run of success. With offices across the UK, US & Australia, they are now looking to bolster the London team with the addition of another Senior Analytics Engineer.
💰 Salary: £80,000
🚀 Industry/Type of business: SaaS platform
🏠 Remote working: 2 days WFH
🧩 Interview process: 3 stages
👏 Company size: ~40
🎯 Working on: Data modelling, transformation, data warehousing, data wrangling - with a small element of statistics & forecasting.
What are we looking for?
- Experience modelling in the data warehouse, multi-step SQL, data wrangling
- The ability to solve ambiguous challenges with data
- The ability to communicate with clients & identify needs
- An understanding of data in relation to dynamic pricing, revenue operations & management, demand forecasting, competitor analysis etc. would be useful!
- SQL, Python, Cloud (GCP, Azure, AWS or Snowflake), Airflow/dbt etc.
Interested in hearing more? Apply!
Senior Analytics Engineer in London employer: Cognify Search
Cognify Search offers an exceptional work environment for the Head of ML & AI, where innovation meets collaboration. With a focus on enhancing customer experience through cutting-edge technology, employees benefit from a culture that prioritises professional growth and teamwork. Located in a dynamic eCommerce hub, this role provides unique opportunities to lead impactful projects while working alongside industry experts.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer in London
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as SQL, Python, and cloud platforms like GCP or AWS. Having hands-on experience or projects showcasing these skills can set you apart during the interview process.
✨Tip Number 2
Prepare to discuss your previous experiences with data modelling and transformation. Be ready to share specific examples of how you've tackled ambiguous challenges using data, as this will demonstrate your problem-solving abilities to the interviewers.
✨Tip Number 3
Since communication with clients is key for this role, practice articulating complex data concepts in simple terms. This will help you convey your understanding of client needs effectively during interviews.
✨Tip Number 4
Research the company’s focus on dynamic pricing and revenue operations. Being knowledgeable about industry trends and how they relate to the role can give you an edge and show your genuine interest in the position.
We think you need these skills to ace Senior Analytics Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data modelling, SQL, and Python. Emphasise any previous roles where you've tackled ambiguous challenges with data, as this is a key requirement for the position.
Craft a Compelling Cover Letter:In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that demonstrate your skills in data warehousing and transformation, and how they align with the company's needs.
Showcase Relevant Skills:Clearly list your technical skills such as SQL, Python, and experience with cloud platforms like GCP or AWS. If you have experience with tools like Airflow or dbt, make sure to highlight that as well.
Prepare for the Interview:Research common interview questions for analytics roles and prepare examples from your past work that showcase your problem-solving abilities and communication skills. Be ready to discuss how you've identified client needs in previous positions.
How to prepare for a job interview at Cognify Search
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL, Python, and cloud platforms like GCP or AWS. Be prepared to discuss specific projects where you've used these skills, as this will demonstrate your technical proficiency.
✨Prepare for Data Challenges
Expect to face questions that assess your problem-solving abilities with data. Brush up on your data modelling and transformation techniques, and be ready to explain how you approach ambiguous challenges.
✨Communicate Effectively
Since the role involves client interaction, practice articulating complex data concepts in a simple manner. Think of examples where you've successfully identified client needs and how you addressed them.
✨Understand the Business Context
Familiarise yourself with concepts like dynamic pricing and demand forecasting. Being able to relate your technical skills to business outcomes will show that you understand the bigger picture and can add value to the company.
