VP Data Engineer

You will build and maintain tools and infrastructure that enable autonomous data pipelines. You will operate platform monitoring, alerting, Kafka, Kubernetes, Terraform, Databricks, Spark, AWS services, dbt, and orchestration systems. You will partner on platform improvements and troubleshoot production issues.

Responsibilities

• Build and maintain tooling and infrastructure for autonomous data pipelines.
• Own monitoring, alerting, and DataOps practices.
• Operate Kafka for event-driven architecture.
• Deploy, own, and maintain infrastructure components with Terraform and Kubernetes.
• Run high-throughput, low-latency processing on Databricks, Spark, and AWS services.
• Support dbt transformations and Airflow orchestration.
• Partner on the design and delivery of platform improvements.
• Troubleshoot production issues and drive fixes.
• Use AI tools to improve productivity, decision-making, and output quality.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years building production data or platform engineering systems.
• Strong Python or Java coding skills.
• Experience operating production data platforms on AWS and supporting downstream teams.
• Hands-on experience with Kubernetes and Terraform.
• Experience operating Kafka or a similar broker in event-driven systems.
• Working knowledge of Databricks, Spark, dbt, and Airflow.
• Knowledge of data modeling, data quality, relational databases, and non-relational databases.
• Experience with CI/CD, testing frameworks, and observability tooling.

Benefits

• Company-paid health and protective benefits for employees and eligible dependents.
• Free virtual coaching and counseling sessions.
• Employee Resource Groups.