job description
Join Eton Properties Philippines as a Senior Data Engineer and play a pivotal role in transforming raw enterprise data into powerful, actionable insights that drive smarter business decisions and next-generation digital experiences. In this dynamic role, you will design, build, and optimize scalable data pipelines, ensuring high-quality data flows seamlessly across our systems.
Based in the vibrant and innovative hub of Bali, Indonesia, you’ll collaborate with cross-functional teams to develop cutting-edge data solutions that empower our organization to stay ahead in a data-driven world. Whether you're enhancing data models, automating workflows, or integrating new technologies, your work will directly impact our ability to deliver exceptional value to stakeholders.
If you’re passionate about big data, cloud technologies, and analytics, and thrive in a fast-paced, collaborative environment, this is your opportunity to make a lasting impact while enjoying the unique work-life balance that Bali offers.
Responsibility
- Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and load large datasets from multiple sources.
- Optimize and automate data workflows to improve efficiency, reliability, and performance.
- Collaborate with data scientists, analysts, and business teams to define data requirements and deliver high-quality datasets.
- Implement and manage data warehouses, lakes, and marts using modern cloud-based solutions (e.g., AWS, GCP, Azure).
- Ensure data integrity, security, and compliance with industry standards and best practices.
- Monitor and troubleshoot data pipeline issues, implementing proactive solutions to minimize downtime.
- Develop and maintain data models, schemas, and metadata to support analytics and reporting needs.
- Stay current with emerging trends in data engineering, AI, and machine learning to drive continuous improvement.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; Master’s degree is a plus.
- Minimum 5 years of experience in data engineering, with a proven track record of building and optimizing data pipelines.
- Proficiency in SQL, Python, or Scala for data manipulation and scripting.
- Experience with big data technologies such as Hadoop, Spark, Kafka, or similar frameworks.
- Hands-on experience with cloud platforms (AWS, GCP, Azure) and their data services (e.g., Redshift, BigQuery, Snowflake).
- Strong understanding of data warehousing concepts, dimensional modeling, and ETL/ELT processes.
- Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform, Docker).
- Excellent problem-solving skills and the ability to work in a collaborative, Agile environment.