Data Analytics Engineer

Role Overview

As a Data Analytics Engineer at Doodle, you will play a key role in establishing a reliable data infrastructure that underpins all product-related decisions. This role involves transforming raw product data into scalable, trustworthy datasets to fuel experimentation, reporting, and innovation across the company.

Key Responsibilities

• Design, develop, and maintain scalable data models and transformation pipelines using dbt and modern data engineering techniques.
• Manage data performance, dependability, and ongoing enhancements of the analytics platform supporting self-service insights.
• Create and update a semantic layer for consistent reporting and ensure accurate, accessible data definitions maintained across teams.
• Take ownership of data quality, validation, testing, monitoring, and governance across the analytics infrastructure.
• Apply best practices in documentation, version control, continuous integration, and automated testing for improved data reliability and security.
• Collaborate with Product Managers and Analysts to support experimentation, funnel and retention analysis, customer insight generation, and reliable measurement frameworks for product launches.
• Enable precise A/B testing by ensuring high-quality event modeling and instrumentation.
• Work closely with cross-functional teams in Engineering, Product, Marketing, Finance, and Leadership to translate business needs into actionable data-driven solutions.
• Advise on analytics architecture, data modeling standards, and foster a culture of data reliability and accessibility.

Qualifications and Skills

• Proven expertise with analytics data modeling frameworks like dbt and orchestration tools such as Airflow.
• Advanced proficiency in SQL and experience handling large-scale analytical datasets.
• Familiar with cloud data warehouses including Amazon Redshift; experience with Athena or Spark is advantageous.
• Strong Python programming skills for data processing and automation tasks.
• Good grasp of dimensional data modeling, database design, and analytics engineering principles.
• Understanding of product analytics, experimentation frameworks, and related tools.
• Commitment to quality through testing, thorough documentation, version control, and continuous integration.
• Excellent problem-solving capabilities with meticulous attention to detail.
• Effective communicator adept at explaining technical concepts to diverse stakeholders.
• Experience collaborating effectively in fast-paced SaaS environments.

Desirable Attributes

• Hands-on experience with Python libraries such as pandas.
• Background in supporting Product Led Growth strategies.
• Experience creating semantic layers or enabling self-service analytics environments.
• Familiarity with product analytics platforms like Amplitude, Mixpanel, or GA4.
• Exposure to modern B2B SaaS industry environments.

Additional Information

Doodle is committed to fostering a diverse and inclusive workplace where equal opportunity is extended to all team members and applicants regardless of age, race, color, disability, religion, gender, or sexual orientation. Our teams thrive on diverse experiences and perspectives to create the best products.

Important: Applications will only be considered from candidates based in Germany or London who have the legal right to work there. Visa sponsorship and relocation assistance are not available for this position.

Selection Process

• Initial application screening followed by BRYQ assessment
• Interview with the Hiring Manager
• Technical assessment phase
• Cross-functional technical interviews
• Final interviews with executive management and human resources