Overview
We are looking for a Senior Data Engineer to help evolve and scale our Data Platform, enabling reliable, high-quality, and self-service analytics across the business.
In this role, you'll work closely with Data Engineers, Machine Learning Engineers, Data Scientists, Product Managers, and business stakeholders to improve our data platform, information architecture, and data pipelines. You'll also help scale our capabilities on DBT and Databricks to support growing business needs.
Responsibilities
- Contribute to the data platform strategy and roadmap.
- Build and maintain efficient, reliable ETL workflows.
- Improve data infrastructure, code structure, and architecture for better maintainability and performance.
- Use AI-assisted engineering tools to improve delivery velocity and code quality.
- Take ownership of technical implementation from design through deployment.
- Support production infrastructure, incident response, and post-mortem activities.
- Collaborate with cross-functional teams to deliver data initiatives.
- Mentor junior engineers and share engineering best practices.
Qualifications
Must Have
- 5+ years of experience in Data Engineering, Data Warehousing, Business Intelligence, or related areas.
- Hands-on experience with Databricks, DBT, and AWS.
- Strong knowledge of data ingestion tools (e.g. Fivetran, Kafka).
- Experience with orchestration tools such as Airflow or Databricks Jobs.
- Understanding of data catalog and lineage tools (e.g. DataHub).
- Experience delivering projects end-to-end, from discovery and planning through development, testing, and deployment.
- Hands-on experience using AI-assisted development tools in day-to-day engineering work.
Nice to Have
- Experience with Infrastructure as Code using Terraform or Kubernetes.
- Experience working in Agile environments (Scrum or Kanban).
- Experience collaborating with cross-functional teams across Product, Engineering, Sales, Service, or Marketing.
