Data Infrastructure Engineer

Job summary

Design, build, and operate scalable data infrastructure that makes data reliable, secure, and accessible to product, engineering, analytics, and security teams. The role includes Kafka and Avro streaming, Airflow batch workflows, Redshift performance and data modeling, cloud infrastructure as code, and improvements to system reliability, data security, cataloging, lineage, and self-service tooling.

Qualifications

• At least 2 years of experience in data platform engineering or scalable software systems
• Experience with Kafka and Avro schema design, serialization, and evolution
• Experience with Redshift and production Airflow, including data modeling and performance tuning
• Cloud and DevOps experience with CI/CD, infrastructure as code, Kubernetes, data lakes, and open table formats
• Experience with observability, incident response, and debugging pipeline failures
• Security-conscious approach to data access, privacy, and secrets
• Clear communication with technical and non-technical stakeholders
• dbt experience is a plus

Responsibilities

• Design, build, and operate scalable infrastructure for data ingestion, transformation, storage, and serving
• Run Kafka and Avro streaming workflows and orchestrate batch workflows in Airflow
• Maintain performant, well-modeled, and cost-effective Redshift systems
• Manage secure, reproducible cloud environments for development, testing, and production
• Own SLOs, runbooks, and alerts for critical data systems
• Protect sensitive data with access controls, encryption, secrets management, and retention policies
• Investigate incidents, lead root-cause analysis, and implement preventative improvements
• Improve data discoverability through cataloging, lineage, ownership, and quality testing
• Build documentation, tooling, and self-service workflows for analytics and engineering teams

Skills

Industry

Relocation