Data Engineer at Sertis

Sertis is a premier Data and AI company headquartered in Bangkok, dedicated to delivering bespoke solutions that range from data infrastructure and business intelligence to advanced forecasting and computer vision. We partner with clients across diverse sectors like manufacturing, banking, and retail, and we are currently looking for a Senior Data Engineer to join our team in a full-time, hybrid capacity based in Thailand.

Responsibilities

• Design and construct scalable data pipelines to ingest, process, and store large volumes of information.
• Partner with cross-functional teams to translate business needs into effective technical data solutions.
• Manage complex data integration from various sources, including APIs, databases, and analytics platforms.
• Ensure the highest standards of data quality, accuracy, and security, including compliance with regulations like PDPA.
• Maintain and optimize existing ETL pipelines while advising on infrastructure improvements.
• Support pre-sales efforts by gathering requirements, defining project scopes, and estimating technical costs.
• Contribute to the growth of our team by participating in recruitment and mentoring junior colleagues.
• Develop comprehensive technical documentation to support project longevity.

Must-haves

• At least 4 years of professional experience in data engineering, specifically in building and maintaining cloud-based infrastructure on platforms like AWS, GCP, or Azure.
• Advanced programming proficiency, with a strong preference for Python.
• Deep expertise in designing Data Lake architectures and utilizing data warehousing tools like BigQuery, Redshift, or Synapse.
• Hands-on experience with big data technologies such as Spark and Hive.
• Proven ability to write and optimize complex SQL queries for large-scale datasets.
• Experience with orchestration tools like Airflow or AWS Step Functions.
• Familiarity with Infrastructure as Code and CI/CD practices using tools like Terraform or Gitlab CI.
• Strong leadership skills and the ability to scope projects independently.
• Fluency in English.

Nice-to-haves

• Relevant cloud data engineering certifications.
• Experience with data streaming technologies and containerization using Docker.
• Background in Agile methodologies such as Scrum or Kanban.
• Knowledge of cloud cost optimization strategies.
• Experience managing multiple concurrent projects.

Benefits

• Hybrid work model to support your work-life balance.
• Flexible working hours to accommodate your personal schedule.
• Opportunities to collaborate with and learn from industry-leading experts in the AI field.
• A culture that prioritizes autonomy, innovation, and continuous professional growth.
• Regular company social outings and events with a supportive, down-to-earth team.
• The chance to solve real-world challenges at the frontier of AI innovation.