At a Glance
- Tasks: Own and enhance our analytics platform for self-service insights and reliable data models.
- Company: Join a dynamic SaaS company focused on innovation and collaboration.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a fast-paced environment with excellent career advancement.
- Why this job: Make a real impact by transforming raw data into actionable insights.
- Qualifications: Strong SQL and Python skills, with experience in data pipelines and analytics platforms.
The predicted salary is between 50000 - 65000 £ per year.
Responsibilities
- Own the analytics platform that enables self-service insights across Doodle.
- Design, build, and maintain scalable analytics data models using dbt and modern data engineering practices.
- Develop reliable transformation pipelines that convert raw product data into trusted, business-ready datasets.
- Own the performance, reliability, and continuous improvement of Doodle’s analytics platform.
- Define, document, and maintain trusted business metrics used across the company.
- Build and evolve a scalable semantic layer that enables consistent reporting and self-service analytics.
- Ensure data definitions remain accurate, accessible, and aligned across teams.
- Own data quality, validation, testing, monitoring, and governance across the analytics stack.
- Implement best practices for documentation, version control, CI, and automated testing.
- Establish standards that improve data reliability, consistency, security, and trust.
- Partner with Product Managers and Analysts to enable experimentation, funnel analysis, retention analysis, and customer insights.
- Support product launches by providing reliable measurement frameworks and trusted analytics.
- Enable accurate A/B testing through high-quality event modelling and instrumentation.
- Work closely with Product, Engineering, Data, Marketing, Finance, and Leadership teams.
- Translate business questions into scalable data models, trusted metrics, and actionable insights.
- Advise teams on analytics architecture, data modelling standards, and best practices.
- Influence product and business decisions by making data reliable, accessible, and easy to use.
Qualifications
- Strong engineering fundamentals with a product mindset and a passion for building trusted, scalable analytics platforms.
- Experience orchestrating modern data pipelines using Airflow or similar workflow tools.
- Advanced SQL skills with experience working on large analytical datasets.
- Experience working with cloud data warehouses such as Amazon Redshift.
- Experience with Athena or Spark is an advantage.
- Strong experience building analytics data models using dbt or similar transformation frameworks.
- Strong Python skills for data processing and automation.
- Familiarity with experimentation frameworks and product analytics.
- Good understanding of dimensional data modelling, database design, and analytics engineering principles.
- Strong problem-solving skills with excellent attention to detail.
- Quality first mindset with experience in testing, documentation, version control, and CI.
- Passion for building reliable, scalable, and maintainable analytics platforms.
- Enjoy collaborating in a fast-moving SaaS environment.
- Comfortable working across Engineering, Product, Analytics, and business teams.
- Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
- Experience with pandas or similar Python data processing libraries.
- Experience supporting Product Led Growth organisations.
- Experience building semantic layers or self-service analytics platforms.
- Experience with product analytics tools such as Amplitude, Mixpanel, or GA4.
- Experience working in a modern B2B SaaS environment.
Data Analytics Engineer employer: Doodle
Doodle is an exceptional employer that fosters a dynamic and inclusive work culture, perfect for those looking to thrive in the B2B SaaS landscape. With a strong emphasis on employee growth, we offer comprehensive training and development opportunities, ensuring our team members can advance their careers while enjoying the flexibility of a hybrid work environment. Join us to be part of a collaborative team that values innovation and customer success, all while making a meaningful impact in the industry.
We think you need these skills to ace Data Analytics Engineer
Data Modelling
SQL
dbt
Python
Airflow
Amazon Redshift
Data Quality Assurance
