Analytics Engineer

What you’ll do

• Develop and maintain scalable and performant data models using dbt, ensuring data is well-structured, rich in analytical value, and ready for analysis
• Design and optimize SQL-based transformation pipelines that deliver high-quality datasets to the business intelligence and analytics teams
• Collaborate with stakeholders (business analysts, product managers) to gather requirements and ensure data models support meaningful business reporting
• Implement business logic in data models to ensure KPIs and business metrics are accurately reflected
• Establish and maintain data quality checks and automated testing to ensure accuracy and consistency across business-critical data
• Continuously monitor and improve the performance of data transformations and queries, ensuring efficiency and scalability
• Maintain clear and comprehensive documentation for data models, ensuring analysts and stakeholders can easily understand and use the data
• Mentor junior team members and actively contribute to developing the team’s skills and best practices in analytics engineering

What you’ll need to succeed

• Strong proficiency in SQL, with experience writing efficient queries to transform, model, and analyze large datasets
• Experience with dbt to build and manage reusable data models
• Ability to translate business requirements into scalable data models aligned with key business metrics
• Familiarity with BI tools like Looker, Tableau, or Power BI and a solid understanding of how to structure data for optimal use in these platforms
• Experience implementing automated data quality checks within data pipelines; Python knowledge is a plus
• Strong communication skills with the ability to collaborate across technical and non-technical teams to deliver solutions that meet business needs.
• Basic knowledge of cloud-based platforms (e.g., Snowflake, BigQuery, Redshift) is advantageous
• Experience working in a remote-first, collaborative environment with a proactive, self-directed approach