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For Companies At a Glance
- Tasks: Join a dynamic team to build and enhance customer data platforms.
- Company: Be part of a leading telecoms company revolutionizing the industry with flexibility.
- Benefits: Enjoy fully remote work with monthly travel expenses covered.
- Why this job: Make an impact by improving data models in a collaborative environment.
- Qualifications: 4+ years in SQL, Python, DBT, and cloud technologies like Snowflake.
- Other info: Engage in a structured interview process to showcase your skills.
The predicted salary is between 60000 - 70000 £ per year.
Senior Analytics Engineer
Hillingdon – Once a month in office
Up to £75,000
Company Overview
Join a fast-growing telecom startup backed by a major industry player. This company is on a mission to revolutionise the mobile industry by prioritising value, flexibility, and mutuality. With an abundance of rich data sets, this is an exciting opportunity for data professionals who thrive on working with large and complex data systems.
This mobile network is known for its unique community-led model, where members help each other with support and even contribute ideas for new features!
The Opportunity
The Data Engineering function is responsible for constructing analytics pipelines and supporting operations across different teams. Currently, they are developing a new metrics catalog within an analytical database, aiming to fully automate the process to integrate seamlessly into regular operations.
In this day to day, you will:
- Designing and developing high-quality data pipelines using DBT and Python.
- Migrating reports from SQL Server to Snowflake.
- Understanding and modeling data points to implement efficient solutions in Snowflake.
- Supporting the build-out of the data warehouse.
- Implementing CI/CD pipelines for streamlined deployment processes.
What You Will Bring
We\’re looking for someone who loves working with data and enjoys solving complex problems.
Must-Haves:
- Solid experience in data modeling (think Data Vault, Kimball, or similar approaches).
- Extensive experience working as a Data Engineer or Analytics Engineer.
- Strong skills in DBT and SQL – you’ll be using these every day!
- Hands-on experience with cloud data warehouses like Snowflake, GCP, Redshift, or BigQuery.
Nice-to-Haves:
- Familiarity with CI/CD pipelines – if you’ve set up automated deployments, even better.
- Understanding of attribution models – knowing how to track and optimise performance is a plus.
- Some exposure to Kafka for real-time streaming – if you’ve worked with it, that’s a great bonus!
Why Join?
This is a fantastic opportunity to be part of an innovative telecom company that values data-driven decision-making and cutting-edge technology. If you are passionate about analytics engineering and want to work with rich datasets in a collaborative environment, this could be the perfect role for you!
- Eco-Friendly Efforts! 🌍 – The company promotes sustainability by encouraging customers to buy refurbished phones and recycle old devices through its phone recycling program.
- Award-Winning Network! 🏆 – This mobile provider has won multiple awards for customer satisfaction and value, often beating big-name competitors in mobile network rankings.
- Powered by a Major Network! 📡 – While operating independently, this provider runs on a well-established network, ensuring solid coverage across the UK.
Senior Analytics Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer
✨Tip Number 1
Familiarize yourself with the specific tools mentioned in the job description, like Snowflake and DBT. Having hands-on experience or projects that showcase your skills with these technologies can set you apart during the interview process.
✨Tip Number 2
Since communication is key for this role, practice explaining complex data concepts in simple terms. This will help you demonstrate your ability to collaborate effectively with both technical and non-technical stakeholders.
✨Tip Number 3
Prepare for the technical interview by brushing up on SQL and Python. Consider working through some real-world problems or case studies that involve data transformation and analytics to showcase your problem-solving skills.
✨Tip Number 4
Research the company’s approach to product analytics and their vision for the telecom industry. Being able to discuss how your experience aligns with their goals will show your genuine interest in the role and the organization.
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Understand the Role: Make sure you fully understand the responsibilities and requirements of the Senior Product Analytics Engineer position. Highlight your experience with SQL, Python, and DBT in your application.
Tailor Your CV: Customize your CV to reflect your relevant experience, especially focusing on your work with cloud technologies like Snowflake and your involvement in data product teams. Use specific examples to demonstrate your skills.
Craft a Strong Cover Letter: Write a cover letter that showcases your communication skills and your ability to work in a team. Mention your experience with ELT pipelines and how you can contribute to improving existing models.
Prepare for Interviews: Anticipate questions related to your technical skills and past experiences. Be ready to discuss your approach to building data warehouses and your familiarity with CI/CD pipelines and real-time streaming technologies.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL, Python, and DBT during the interview. Be prepared to discuss specific projects where you've used these technologies, especially in relation to data ingestion and transformation.
✨Prepare for the Take-Home Exercise
The take-home exercise is a crucial part of the interview process. Practice similar exercises beforehand, focusing on building efficient ELT pipelines and working with Snowflake. This will help you feel more confident and showcase your skills effectively.
✨Communicate Clearly
Strong communication skills are essential for this role. During the interviews, make sure to articulate your thoughts clearly, especially when discussing how you would collaborate with team members and stakeholders on data projects.
✨Understand the Company Culture
Research the company's values and culture before the culture fit interview. Be ready to discuss how your personal values align with theirs and provide examples of how you've contributed to a positive team environment in the past.
