job description
Join ScienTec Consulting as a Senior Data Engineer and lead the design, development, and optimization of scalable data pipelines in a dynamic, cloud-first environment. This role offers the unique opportunity to work remotely from the vibrant hubs of Bali, Indonesia, including Canggu, Ubud, Denpasar, and more, while collaborating with a global team to drive data-driven decision-making.
With 6+ years of experience in ELT/ETL processes, Python, and AWS, you will architect robust data solutions, ensuring high performance, reliability, and security. Your expertise will empower businesses to harness the full potential of their data, transforming raw information into actionable insights.
We are looking for a proactive problem-solver with a passion for innovation, cloud technologies, and best practices in data engineering. If you thrive in a collaborative, fast-paced environment and want to make an impact with cutting-edge data infrastructure, this is the role for you.
Responsibility
- Design, build, and maintain scalable ETL/ELT pipelines using AWS services (Glue, Lambda, Redshift, S3, etc.) and Python frameworks (Pandas, PySpark).
- Optimize data workflows for performance, cost-efficiency, and reliability, ensuring seamless data integration across sources.
- Develop and enforce data governance, quality, and security standards in compliance with industry best practices.
- Collaborate with cross-functional teams (data scientists, analysts, and software engineers) to deliver end-to-end data solutions.
- Automate data processes using CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation).
- Monitor and troubleshoot data pipelines, implementing proactive alerting and logging mechanisms.
- Mentor junior engineers and contribute to technical documentation and knowledge-sharing initiatives.
- Stay ahead of industry trends in big data, cloud computing, and data engineering to drive continuous improvement.
Qualifications
- 6+ years of hands-on experience in data engineering, with a focus on ELT/ETL, Python, and AWS.
- Proficiency in AWS data services (Redshift, Glue, Athena, Kinesis, RDS) and Python libraries (Pandas, NumPy, PySpark).
- Experience with data warehousing solutions (Snowflake, BigQuery, or Redshift) and big data frameworks (Spark, Hadoop).
- Strong knowledge of SQL, NoSQL databases, and data modeling techniques.
- Familiarity with containerization (Docker, Kubernetes) and orchestration tools (Airflow, Luigi).
- Experience with version control (Git) and CI/CD pipelines (Jenkins, GitHub Actions).
- Excellent problem-solving skills and the ability to work in Agile/Scrum environments.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).