Aurora is looking to build scalable and reliable data systems to enable data-driven insights and product innovation for their self-driving technology.
Requirements
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 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.
Experience with data warehousing solutions like Snowflake or data lake architectures.
Responsibilities
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.
Other
3+ years of professional experience in software engineering, with a focus on data-related projects.
Able to systematically approach open-ended questions to identify pragmatic data solutions that scale
Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment
Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders
A passion for building elegant, scalable, and maintainable systems.
