Data Engineer

Responsibilities

• Work with business partners and stakeholders to understand data requirements
• Work with engineering, product teams and 3rd parties to collect required data
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Develop and implement data quality checks, conduct QA and implement monitoring routines
• Improve the reliability and scalability of ETL processes
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

Requirements

• 2+ years of professional experience in data engineering, business intelligence, or a similar role
• Proficiency in Python or Java
• 2+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie or Azkaban using AWS/GCP
• Expert in Database fundamentals, SQL and distributed computing
• 2+ years of experience with the Distributed data ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink
• Experience with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms
• Knowledge of reporting tools such as Tableau, Superset or Looker
• Excellent communication skills and ability to work in a fast-paced environment
• Must be located near the São Paulo engineering hub

About the Company

DoorDash is building the world’s most reliable on-demand logistics platform. We are a technology and logistics company that empowers local economies, helping Dashers, merchant partners, and consumers connect seamlessly.