Data Engineer, Data Pipelines & Infra (Hybrid)

AURORA; Mountain View (CA); Hybrid; USD 116,000 - 174,000; Full time

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

Aurora is seeking a talented Software Engineer to join our data engineering and infrastructure team. You will design and maintain scalable data pipelines, build data lake/warehouse infrastructure, and work with ETL/ELT processes to support data-driven insights and product innovation.

You will collaborate with data scientists, analysts, autonomy engineering, and product teams to understand data needs and deliver reliable, secure data solutions at massive scale.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 1+ years of professional experience in software engineering, with a focus on data-related projects.
• Proficiency in Python, Go or C++.
• Experience with big data processing frameworks (Spark, Flink, Kinesis, etc.).
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and data services (S3, Redshift, BigQuery, Glue).
• Strong knowledge of SQL and relational/NoSQL databases.
• Experience with DBT and visualization tools.
• Experience with Apache Airflow for orchestration.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes into our data warehouse.
• Develop and manage data infrastructure components using AWS and Terraform.
• Collaborate with data scientists, analysts, and product teams to meet data needs.
• Optimize data processing for performance, reliability, and cost-efficiency.
• Implement monitoring, logging, and alerting for data pipelines and infra.

Skills

Python

Go

C++

SQL

Airflow

AWS

Terraform

Education

Bachelor's degree in Computer Science or related field

Tools

Data pipelines

Job description

Aurora is seeking a talented Software Engineer to join our data engineering and infrastructure team. You will design and maintain scalable data pipelines, build data lake/warehouse infrastructure, and work with ETL/ELT processes to support data-driven insights and product innovation.

You will collaborate with data scientists, analysts, autonomy engineering, and product teams to understand data needs and deliver reliable, secure data solutions at massive scale.