job description
Join CARiNG Pharmacy as a Senior Data Engineer and play a pivotal role in transforming raw data into actionable insights that drive business growth. Based in the vibrant hub of Canggu, Bali, you'll collaborate with cross-functional teams to design, build, and optimize scalable data pipelines, ensuring seamless data flow across our cloud-based infrastructure.
At CARiNG Pharmacy, we leverage cutting-edge technologies to enhance healthcare solutions. As a Senior Data Engineer, you'll work with modern ETL/ELT frameworks, cloud platforms (AWS/GCP/Azure), and big data tools to support data-driven decision-making. This role offers the opportunity to innovate in a dynamic environment while contributing to meaningful projects that impact healthcare delivery.
If you're passionate about data architecture, performance optimization, and solving complex data challenges, we'd love to hear from you. Enjoy the flexibility of working in Bali's thriving tech community while advancing your career with a forward-thinking company.
Responsibility
- Design, develop, and maintain scalable ETL/ELT pipelines to integrate data from multiple sources.
- Optimize data storage solutions, including data lakes, warehouses, and databases, for performance and cost efficiency.
- Collaborate with data scientists and analysts to ensure data accessibility and quality for analytics and reporting.
- Implement data governance and security best practices to protect sensitive healthcare data.
- Monitor and troubleshoot data pipeline performance, ensuring high availability and reliability.
- Automate data workflows using tools like Airflow, Luigi, or similar orchestration frameworks.
- Stay updated with emerging data technologies and recommend improvements to the data infrastructure.
- Mentor junior engineers and contribute to team knowledge-sharing initiatives.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in data engineering, with a focus on cloud-based solutions (AWS, GCP, or Azure).
- Proficiency in SQL, Python, and Scala for data processing and scripting.
- Hands-on experience with big data tools (Spark, Hadoop, Kafka) and data warehousing (Snowflake, Redshift, BigQuery).
- Strong understanding of data modeling, ETL/ELT processes, and workflow automation.
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines is a plus.
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Familiarity with healthcare data standards (e.g., HL7, FHIR) is advantageous.