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- Tasks: Own the dbt layer and shape analytics best practices in a growing team.
- Company: Join an innovative platform connecting travellers with reliable home care services.
- Benefits: Enjoy remote work flexibility and be part of a purpose-led business.
- Why this job: Make a real impact on data strategy while enhancing travel and pet care experiences.
- Qualifications: Strong SQL skills, experience with dbt, and familiarity with cloud data warehouses required.
- Other info: Ideal for those passionate about data transformation in a high-growth environment.
The predicted salary is between 40000 - 48000 £ per year.
This innovative, subscription-based platform brings together a global community of individuals with complementary needs: those seeking flexible travel opportunities and those requiring reliable care for their home and animals. The model is built around trust and mutual benefit, offering a unique alternative to traditional services by focusing on shared value rather than direct transactions.
The company is at an exciting stage of data transformation. Over the past six months, they’ve built the foundations of a modern data platform, including hiring a data manager to oversee governance and integrations, a data engineer, and most recently, a data scientist. With dbt introduced as part of a broader tech overhaul, the team is now looking for a dedicated Analytics Engineer to take ownership of the dbt layer and play a key role in shaping analytics best practices across the business.
As the team scales, there’s a clear need for someone to focus solely on the analytics engineering function. Currently, analytics work is shared across the team, but performance bottlenecks, a lack of consistency, and the opportunity to implement best practice modelling highlight the need for a specialist. This role will be instrumental in building a reliable and scalable production environment on top of a growing set of raw data sources.
Tech Stack and Environment:
- Data Warehouse: Redshift
- Modelling: dbt (recently onboarded, still early-stage)
- ETL & Integration: Fivetran, with plans to scale
- Architecture: Medallion
- Dashboarding & Visualisation: Mode Analytics (SQL-based)
Ideal Background:
- Strong SQL skills with hands-on experience in dbt and modern cloud data warehouses (e.g. Redshift, Snowflake, BigQuery)
- Familiarity with ELT tools (e.g. Fivetran), BI tools (e.g. Looker, Tableau, Power BI), and Git-based workflows
- Solid understanding of data modelling, warehousing principles, and analytics best practices
- Experience working cross-functionally with strong communication skills
Nice to have:
- Python, AWS/GCP/Azure, Medallion Architecture, Databricks, and knowledge of data governance or experience in high-growth environments
This is a fantastic opportunity to join a purpose-led business in a high-impact role, helping to shape the data strategy of a company making travel more accessible and pet care more personal.
Analytics Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Familiarise yourself with dbt and its best practices. Since this role focuses on taking ownership of the dbt layer, demonstrating your understanding of dbt's functionalities and how it integrates with data warehouses like Redshift will set you apart.
✨Tip Number 2
Showcase your SQL skills through practical examples. Prepare to discuss specific projects where you've used SQL to solve complex problems or improve data processes, as strong SQL proficiency is a key requirement for this position.
✨Tip Number 3
Network with professionals in the analytics engineering field. Engaging with others who work in similar roles can provide insights into industry trends and expectations, which can be beneficial during interviews.
✨Tip Number 4
Prepare to discuss your experience with cross-functional collaboration. This role requires strong communication skills, so be ready to share examples of how you've successfully worked with different teams to achieve common goals.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong SQL skills and hands-on experience with dbt and cloud data warehouses. Emphasise any relevant projects or roles that showcase your ability to work with ELT tools and BI tools.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company’s mission. Discuss how your background aligns with their needs, particularly in building a reliable and scalable production environment.
Showcase Relevant Experience: When detailing your work experience, focus on specific achievements related to analytics engineering, data modelling, and cross-functional collaboration. Use metrics where possible to demonstrate your impact.
Highlight Soft Skills: Since strong communication skills are essential for this role, include examples of how you've successfully worked with different teams or stakeholders. This will show that you can effectively contribute to a collaborative environment.
How to prepare for a job interview at Harnham
✨Showcase Your SQL Skills
As an Analytics Engineer, strong SQL skills are crucial. Be prepared to discuss your experience with SQL in detail, including specific projects where you've used it to solve complex problems or improve processes.
✨Demonstrate Your dbt Knowledge
Since the company is looking for someone to take ownership of the dbt layer, make sure to highlight your hands-on experience with dbt. Discuss how you've implemented best practices in previous roles and any challenges you've overcome while using dbt.
✨Understand the Tech Stack
Familiarise yourself with the company's tech stack, especially Redshift and Fivetran. Be ready to explain how you've worked with similar tools and how you can contribute to building a reliable and scalable production environment.
✨Communicate Cross-Functionally
Strong communication skills are essential for this role. Prepare examples of how you've successfully collaborated with different teams in the past, and be ready to discuss how you would approach working cross-functionally in this new position.
