Data Engineer

As a Data Engineer, you will play an important role in the Data Infrastructure team, which is responsible for building and maintaining a scalable, robust, self-service analytics platform.

What you'll do

• Maintain and improve the ingestion pipeline to reliably deliver billions of events daily within a defined SLA.
• Support teams in building and optimizing complex pipelines.
• Work closely with other teams to identify platform pain points and problems.
• Develop new tools and frameworks to improve the data platform.
• Collaborate with data scientists and data analysts to support their production work.
• Work on projects such as building an ML platform and streaming use cases.
• Establish best practices and processes for software and data development.

What you bring

• 3+ years of data engineering experience.
• Experience with an orchestration tool, such as Airflow.
• Experience working with large datasets.
• Experience building complex ETL pipelines.
• Experience with cloud providers such as GCP, AWS, or Azure.
• Strong Spark programming skills 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-motivation and a proven ability to take initiative, own problems, and solve them.

Must-have experience

• Hands-on experience building, scaling, and operating production-grade data platforms or data infrastructure, including reliability, observability, performance, and self-service capabilities.

Nice to have

• Experience 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.