Data Engineer

Title: Data Engineer Location: Remote Opportunity (Candidates from San Francisco area highly preferred) Terms of Employment • W2 Contract, 3 Months • Remote Opportunity (Candidates from San Francisco area highly preferred) • Shift Schedule: 08:00 AM-05:00 PM Overview Data powers all the decisions we make. It is the core of our business, helping us create a great transportation experience for our customers, and providing insights into the effectiveness of our services and products. Focusing on developing ETL pipelines that support decision-making processes for demand, finance and competitive data. Your contributions will help data scientists, analysts, and business leaders make informed decisions. You will need to evaluate multiple approaches, and implement solutions based on fundamental principles, best practices, and supporting data. By architecting, building, and launching robust data pipelines, you will enable seamless access to insights that fuel critical functions such as Analytics, Data Science, and Engineering. Responsibilities • Build core business data pipelines. • Design data models and schemas to meet business and engineering requirements. • Define and implement data quality checks to ensure ongoing data consistency. • Perform SQL tuning to optimize data processing performance. • Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency. • Conduct code reviews to uphold code quality standards. • Produce high quality documentation to facilitate ownership transfer and ongoing support. • Collaborate with internal and external partners to remove blockers, provide support, and achieve results. • Develop, implement, and maintain robust Airflow ETL pipelines to support business and product decisions. • Productionalize SQL and business logic, and perform data modeling to optimize data structures. • Optimize and troubleshoot unhealthy pipelines to ensure data reliability and performance. • Implement data quality validation frameworks to maintain data integrity. • Build essential data feeds, such as a lifetime value (LTV) pipeline for writers, and create reliable data sources for dashboards. • Collaborate closely with data scientists and engineers on the writer team to support their data needs. • Work with the central data platform team for technical guidance and code reviews. Required Skills & Experience ● 5+ years of professional experience in data engineering or a related field. ● Strong expertise in SQL and experience with Spark and/or Trino. ● Proficiency in Python. ● Strong data modelling skills and a deep understanding of ETL processes. ● Experience building and optimizing complex data models and pipelines. ● Extensive experience with Apache Airflow for building and managing ETL pipelines. ● Familiarity with the modern data stack, including Hive-based or partitioned data lake structures. ● Strong sense of ownership and accountability for your work. ● Excellent critical thinking and problem-solving skills.