Senior Software Engineer (Data Engineering and Infrastructure)

Job description

Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.

Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.
Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.
Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.
Optimize data processing systems for performance, reliability, and cost-efficiency.
Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.
Champion best practices in data governance, data quality, and security.
Work closely with other senior team members and management to improve the data ecosystem toolings, refine user experience, and continuously polish team roadmap.

Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
5+ years of professional experience in software engineering, with a focus on data-related projects.
Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).
Solid experience with big data processing frameworks like Presto/Trino, EMR, Apache Spark, Flink, Kinesis Data Stream, or similar technologies.
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).
Strong knowledge of SQL and experience working with relational and NoSQL databases.
Intermediate knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools
Experience with building and managing data pipelines using an orchestrator like Apache Airflow.