Senior Data Platform Engineer: Scalable Pipelines

Aurora; San Francisco (CA); Hybrid; USD 146,000 - 260,000; Full time

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

Aurora is seeking a talented Software Engineer to join the data engineering and infrastructure team. You will design, build, and maintain scalable data pipelines, data lakes, and data warehouses to support insights and product development.

You will work with AWS, Terraform, and modern data tooling to ensure data is high quality, secure, and accessible at massive scale. This role requires strong collaboration across data scientists, analysts, and product teams.

Qualifications

• Master's degree or equivalent practical experience in a related field.
• 5+ years of software engineering experience with a data focus.
• Proficiency in Python, Go or C++, and SQL/NoSQL databases.
• Experience with data processing frameworks and cloud data services.

Responsibilities

• Design, build, and maintain robust data pipelines and ETL/ELT processes into our data warehouse.
• Develop and manage data infrastructure using AWS and IaC tools like Terraform.
• Collaborate with data scientists, analysts, autonomy teams, and product teams.
• Optimize data processing for performance, reliability, and cost-efficiency.
• Implement monitoring, logging, and data governance practices.

Skills

Data pipelines

ETL/ELT

Python/Go/C++

Big data frameworks

SQL/NoSQL

Cloud platforms

Airflow

Data governance

Communication

Education

Master's degree in CS/Engineering

Tools

Terraform

AWS

Redshift

BigQuery

S3

Glue

Airflow

Job description

Aurora is seeking a talented Software Engineer to join the data engineering and infrastructure team. You will design, build, and maintain scalable data pipelines, data lakes, and data warehouses to support insights and product development.

You will work with AWS, Terraform, and modern data tooling to ensure data is high quality, secure, and accessible at massive scale. This role requires strong collaboration across data scientists, analysts, and product teams.