Analytics Engineer II

Skills this role screens for

About the role

As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users. As an Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. You will work closely with data engineers to build scalable data pipelines and collaborate with analysts to ensure data is actionable and insightful. • Design, build, and maintain clean, efficient, and scalable data models in SQL and dbt. Optimize query performance and data processing efficiency. • Ensure data is structured to support self-service analytics and business intelligence. • Work closely with data engineers to define data requirements and enhance ETL pipelines. • Partner with product analysts, data scientists, and business teams to ensure data meets analytical and reporting needs. • Implement and enforce data quality best practices to ensure accuracy and consistency.  • Develop and maintain data transformation workflows using dbt, SQL, and cloud-based data platforms.  • Automate data validation and reporting processes. • Monitor data integrity and troubleshoot data issues proactively. Advocate for best practices in documentation, testing, and version control. • Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required. • 3+ years of hands-on experience in data modeling using dbt. • Strong proficiency in Python, SQL and experience with dbt for data modeling. • Experience working with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift). • Familiarity with version control (Git) and CI/CD practices for data workflows. • Understanding of data engineering principles, including ETL/ELT processes.