job description
Join PERSOL as a Senior AI Data Engineer and lead the development of cutting-edge ETL/ELT pipelines that power AI-driven solutions in one of Asiaâs most dynamic tech hubsâBali, Indonesia.
In this role, youâll design, optimize, and scale data infrastructure to handle large-scale datasets, ensuring seamless data flow for machine learning models and business intelligence. Your expertise in SQL, data warehousing, and cloud platforms will drive innovation, enabling real-time analytics and predictive insights.
Why Bali? Work in a vibrant, tropical environment with a thriving expat and tech community, blending professional growth with an unmatched quality of life. Whether you're based in Cangguâs digital nomad hub or the cultural heart of Ubud, youâll collaborate with global teams while enjoying Baliâs world-class lifestyle.
If youâre passionate about data engineering, AI integration, and building scalable systems, this is your chance to make an impact with a leading multinational corporation.
Responsibility
- Design, develop, and optimize ETL/ELT pipelines to process and transform large-scale structured and unstructured data.
- Build and maintain data warehouses, data lakes, and real-time data processing systems for AI/ML applications.
- Collaborate with data scientists and analysts to ensure high-quality, accessible data for modeling and reporting.
- Implement data governance, security, and compliance best practices (e.g., GDPR, CCPA).
- Automate data workflows using Airflow, Spark, or similar tools to improve efficiency and scalability.
- Monitor pipeline performance, troubleshoot issues, and optimize queries for cost and speed.
- Stay ahead of industry trends in big data, cloud computing (AWS/GCP/Azure), and AI-driven data engineering.
- Document data architectures, processes, and standards for cross-team alignment.
Qualifications
- 5+ years of experience in data engineering, with a focus on ETL/ELT pipelines and large datasets.
- Expert-level SQL skills (complex queries, optimizations, window functions).
- Hands-on experience with Python, Scala, or Java for data processing (Pandas, PySpark, etc.).
- Proficiency in cloud platforms (AWS Redshift, Google BigQuery, Azure Synapse) and big data tools (Hadoop, Spark, Kafka).
- Experience with data warehousing solutions (Snowflake, Redshift, BigQuery) and orchestration tools (Airflow, Dagster).
- Familiarity with MLOps, data versioning (DVC), and CI/CD pipelines for data products.
- Strong problem-solving skills and ability to work in agile, cross-functional teams.
- Bachelorâs or Masterâs degree in Computer Science, Data Engineering, or a related field.