Data Engineer

As a Data Engineer, you will play an important role in the Data Infrastructure team, responsible for building and maintaining a scalable, robust, self-service analytics platform. • Maintain and improve the ingestion pipeline to reliably deliver billions of events daily within a defined SLA. • Support teams in building and optimizing complex data pipelines. • Work closely with other teams to identify pain points and problems around the data platform. • Develop new tools and frameworks to improve the data platform. • Collaborate closely with data scientists and data analysts to support their work in production. • Work on large-scale initiatives such as building an ML platform and streaming use cases. • Establish best practices and processes around software and data development. • 3+ years of experience in data engineering. • Experience working with an orchestration tool, e.g. Airflow. • Experience working with large datasets. • Experience building complex ETL pipelines. • Experience working with cloud providers such as GCP, AWS, or Azure. • Strong programming skills in Spark with Scala and Python. • Experience with CI/CD tools such as Jenkins and Git. • Strong understanding of software engineering practices and principles. • Excellent problem-solving and communication skills. • Self-motivated, proactive, and able to take ownership of problems and drive them to resolution. Hands-on experience building, scaling, and operating production-grade data platforms or data infrastructure, including reliability, observability, performance, and self-service capabilities. • Experience working with messaging systems such as Kafka. • Knowledge of Kubernetes. • Hands-on experience with a streaming platform. • Experience managing a data warehouse in BigQuery or Redshift.