About the role
We are hiring a Senior Data Engineer to lead and grow our Data Engineering team. This role is ideal for an experienced data engineering professional who has a strong technical foundation and a track record of delivering scalable data platforms in fast-paced environments.
Responsibilities:
- Drive execution of the data engineering roadmap in alignment with business priorities.
- Lead and mentor a team of data engineers, supporting their growth and ensuring high-quality delivery.
- Design, build, and maintain scalable data pipelines (batch and streaming).
- Develop and operate high-throughput, low-latency data processing systems.
- Work within the Databricks and Spark ecosystem to support large-scale data workloads.
- Build and maintain cloud-native data solutions on AWS.
- Leverage dbt for transformation, data modelling, testing, and documentation.
- Use Airflow (or similar orchestration tools) to manage and schedule data workflows.
- Establish and enforce best practices around code quality, testing, CI/CD, monitoring, and reliability.
- Collaborate closely with product, analytics, and infrastructure teams to deliver impactful data solutions.
- Contribute to technical design decisions and continuously improve system performance and developer productivity.
Requirements:
- Bachelor's or master's degree in computer science, Engineering, or a related field.
- 5+ years of experience in data engineering or distributed systems.
- Strong hands-on experience with AWS, Databricks/Spark, and modern data architecture.
- Experience building and operating both batch and streaming data pipelines.
- Hands-on experience with dbt for transformations and Airflow (or similar) for orchestration.
- Solid understanding of data modelling, data quality, and production data systems.