What you will do:
As Data Engineering Manager you are responsible for:
- Manage, mentor, and grow a team of skilled data engineers proactively, with continuous feedback, thought leadership, partnership, and formal reviews on software design, team goals and coding standards.
- Lead the development and implementation of data products at scale, leveraging data mesh concepts such as distributed data ownership, by guiding the team and by being hands-on (50/50).
- Contribute to architectural designs which can improve the efficiency and flexibility of services
- Provide development best practices and technical solutions for the data engineering team
- Ensure the development of high-quality code through active participation in code and design reviews.
- Cooperate with product engineers, analysts and data scientists to transform data into actionable insights, features, and models and integrate data back into our product.
- Create a framework to plan and balance priorities between stakeholder requirements, platform improvements, and service requests.
- Ensure data quality across data products and systems including monitoring by defining and managing SLAs.
- Influence the performance of our pipelines to continuously ensure the reliability and efficiency of our data products.
- Oversee data governance in the organization.
- Facilitate team rituals including, stand-ups, planning, demos, backlog refinement, and retrospectives.
- Stay up-to-date with emerging data technologies and industry best practices, with a focus on data mesh concepts and incorporate them into our organisation as appropriate
What you will need:
- Bachelor’s degree or equivalent experience in Computer Science, Information Technology, Engineering or related fields.
- 5+ years of engineering experience for data systems at scale.
- 2+ years of experience with people management
- Deep knowledge of distributed computing technologies, e.g. Kafka, Flink, Spark, Hive, Presto, Druid/Imply.
- Strong programming skills (Python preferred) and experience with data infrastructure components including Kubernetes and Docker.
- Solid track record of solving business challenges with strategic thinking, working across departments and solving challenges in and out of engineering.
- Experience in building real-world data pipelines
- Strong SQL and Python.
- Experience with DevOps practices, CI/CD, and SRE mindset.
- Excellent written and verbal communication in English (Thai is a plus)
- Based in Thailand, or willing to relocate.