Data Engineer
Scale.jobs
- Seattle, Washington, United States
- Seattle, Washington, United States
Über
The engineer will collaborate closely with data scientists, software engineers, and product managers to translate complex business requirements into high-performance, reliable data architectures.
Key Responsibilities
Design, implement, and maintain scalable batch and real-time data pipelines using Apache Spark, Kafka, and Airflow
Architect and optimize data models within the cloud data warehouse (Snowflake/BigQuery) to support analytical and operational workloads
Implement automated data quality testing frameworks to monitor pipeline health, data integrity, and schema evolution
Collaborate with backend engineering teams to integrate transactional database schemas and event streams into the data lakehouse
Optimize query performance, infrastructure costs, and resource allocation across the entire data platform
Establish CI/CD pipelines and deployment best practices for data infrastructure code using Terraform and Git
What We Are Looking For
3-6 years of experience in data engineering, backend engineering, or a highly quantitative technical role
Strong proficiency in writing production-grade Python or Scala, and advanced, highly-optimized SQL
Hands-on experience with modern workflow orchestration tools (Apache Airflow, Prefect, or Dagster) and distributed processing engines (Spark, Flink, or Trino)
Familiarity with cloud-native data warehousing solutions (Snowflake, BigQuery, or Redshift) and lakehouse architectures (Delta Lake, Apache Iceberg)
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field
Bonus: Experience with dbt (data build tool), infrastructure-as-code (Terraform), or containerized deployments using Docker and Kubernetes
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Sprachkenntnisse
- English
Hinweis für Nutzer
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