Senior Data Engineer: Scalable Pipelines & AI-Driven Data

DoorDash USA; Ciudad de México; On-site; MXN 900,000 - 1,400,000; Full time

Job summary

DoorDash is seeking an experienced Data Engineer to join the Tax Data Mart team. You will own data ingestion, transformation, and quality across the data pipelines that power analytics and decision-making for the company.

You will build scalable data systems, work with SQL, Python, and modern tools like Snowflake, DBT, Airflow, Spark, and Kafka, and collaborate with analytics and data science partners to drive impact.

This role requires 5+ years in data engineering and a CS/IT/engineering degree.

Qualifications

• 5+ years of experience in data engineering or similar role.
• Experience using DBT or a similar product to manage data flows.
• Experience with Claude, Cursor and AI tools.
• Proficiency in SQL with Snowflake.
• Proficiency in Python for building data pipelines.
• Experience with modern data stack and orchestration tools (Airflow, Spark, Kafka).
• Strong attention to detail and communication skills.
• CS/IT/Engineering degree.

Responsibilities

• Design, build, and maintain scalable data pipelines (ETL/ELT).
• Develop and optimize data models and warehouse structures.
• Collaborate with analytics, data science, and business partners.
• Identify and document requirements for new initiatives and enhancements.
• Leverage AI-assisted tooling to automate data tasks and pipelines.
• Monitor data quality, reliability, and observability.

Skills

SQL

Python

ETL/ELT

Data modeling

Data quality

Problem solving

Project management

Education

Bachelor's degree in Computer Science / IT / Engineering

Tools

Snowflake

DBT

Airflow

Spark

Kafka

Job description

DoorDash is seeking an experienced Data Engineer to join the Tax Data Mart team. You will own data ingestion, transformation, and quality across the data pipelines that power analytics and decision-making for the company.

You will build scalable data systems, work with SQL, Python, and modern tools like Snowflake, DBT, Airflow, Spark, and Kafka, and collaborate with analytics and data science partners to drive impact.

This role requires 5+ years in data engineering and a CS/IT/engineering degree.