What We're Looking for:

We are looking for people who are passionate about delivering self-driving (L4) products that make the way we move safer, faster, and more efficient. We seek mission-driven, highly skilled people with deep experience in fast-paced, rapidly growing, tech development environments. We are looking for a Technical Lead Manager to build up a team of data engineers to develop and deploy world-class solutions software for next-generation self-driving systems.

What Success Looks Like:

• Lead a team of data engineers to build algorithm-heavy data pipelines.
• Build end-to-end data pipelines from raw data to visualizations.
• Build a workflow orchestration platform to be used by other developers.
• Partner with other development teams to build metrics pipelines.
• Aid in setting the overall vision and core data infrastructure for the company.
• Experience leading a team as a technical lead or manager.
• Hands-on experience implementing data pipeline infrastructure for data ingestion and transformation near real-time availability of data for applications, BI analytics, and ML pipelines.
• Experience designing optimized solutions for large datasets.
• Expert level working knowledge of Data Lake technologies, data storage formats (Parquet, ORC, Avro), and query engines (Athena, Presto, Dremio) and associated concepts for building optimized solutions at scale.
• Expert level in one of the following programming languages or similar- Python, Java, Go.
• Working experience with BI tools like Apache Superset or Tableau.
• Experience in designing data streaming and event-based data solutions (Kafka, Kinesis, SQS/SNS or the like).
• Working experience with cloud-based data warehouses like (Greenplum, RedShift, Azure SQL Data Warehouse, etc).
• Experience with data pipelines tools (Flink, Spark or like) and orchestration tools such as Airflow.
• Knowledge and experience designing solutions with cloud-native AWS Cloud services (EC2, EMR, RDS, EKS etc.) as well as deploying alternative solutions for appropriate use cases.
• Familiarity with cloud-native AWS Cloud services (EC2, S3,DynamoDB,EMR, RDS, EKS etc.) as well as deploying alternative solutions for appropriate use cases.