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PT SMART,Tbk

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Cloud Data Engineer

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Summary

Designs, builds, and maintains scalable ETL/ELT data pipelines and data warehouse solutions on cloud platforms (mainly AWS and Microsoft Fabric) using SQL and Python, supporting BI and analytics teams and leveraging AI-powered coding tools. Requires 4+ years of data engineering experience.

We are looking for an experienced and highly motivated Cloud Data Engineer to join our Data Engineering team. The ideal candidate will be responsible for designing, developing, implementing, and maintaining scalable and reliable data pipelines in cloud environments.

The candidate should have strong hands-on experience in ETL/ELT development, Data Warehouse architecture, SQL programming, and Python development. You will work closely with data science, data analysts, and other technology teams to build and optimize data integration processes that support business intelligence, analytics, and data-driven decision-making.

We are also looking for someone who is comfortable leveraging AI-powered tools to improve development productivity, automate repetitive tasks, and enhance overall engineering efficiency.

Key Responsibilities

  • Design, develop, implement, and maintain robust ETL/ELT data pipelines to support enterprise data integration and analytics requirements.
  • Develop and optimize SQL queries, complex stored procedures, and database processes to ensure efficient data extraction, transformation, and loading.
  • Design, build, and maintain Data Warehouse solutions, including data models, data structures, and data integration workflows.
  • Develop and maintain data processing scripts and automation using Python programming language.
  • Implement and manage data pipelines and data solutions on cloud platforms, mainly AWS and Microsoft Fabric.
  • Monitor, troubleshoot, and optimize data pipelines to ensure data quality, reliability, performance, and availability.
  • Collaborate with cross-functional teams to understand business requirements and translate them into effective technical data solutions.
  • Apply best practices in data engineering, including data security, governance, performance optimization, and process automation.
  • Leverage AI-powered development tools to accelerate coding, troubleshooting, documentation, and data engineering activities.
  • Continuously explore and recommend new technologies, tools, and approaches to improve the organization’s data engineering capabilities.

Requirements & Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Information Systems, or a related field.
  • Minimum 4 years of professional working experience as a Data Engineer, with hands-on experience in developing and managing ETL/ELT data pipelines.
  • Strong understanding of Data Warehouse concepts, architecture, data modelling, and data integration processes.
  • Strong proficiency in SQL, including complex queries, query optimization, and ETL stored procedure development.
  • Good programming skills in Python, particularly for data processing, transformation, and automation.
  • Hands-on experience working with at least one major cloud platform:
  • Amazon Web Services (AWS)
  • Familiarity with cloud-based data services, data storage, and data processing technologies.
  • Ability and willingness to leverage AI-powered tools (e.g., Kiro, GitHub Copilot, or similar AI coding assistants) to improve development efficiency and productivity.
  • Strong analytical and problem-solving skills, with the ability to troubleshoot complex technical issues.
  • Good communication skills and the ability to work independently as well as collaboratively within a team.

Preferred / Added Advantages

  • Experience working with cloud-based Data Warehouse platforms such as Amazon Redshift, Microsoft Fabric
  • Familiarity with workflow orchestration and scheduling tools such as Apache Airflow or similar platforms.
  • Experience with big data technologies and distributed data processing frameworks such as Apache Hadoop or Apache Spark.
  • Familiarity with Git, version control, and CI/CD practices for data engineering development.
  • Experience implementing data quality monitoring and automated data validation processes.
  • Hands-on experience with ETL tools such as Talend or Microsoft SQL Server Integration Services (SSIS).

PT SMART Tbk (SMART) is one of the largest, publicly-listed, integrated palm-based consumer companies in Indonesia committed to sustainable palm oil production.

SMART’s palm oil plantations cover more than 138,000 hectares (including smallholder farmers). Our primary activities are cultivating and harvesting oil palms, processing fresh fruit bunches (FFBs) into crude palm oil (CPO) and palm kernel, and refining CPO into value-added products such as cooking oil, margarine, and shortening. We operate 16 mills, four kernel crushing plants and four refineries across Indonesia.

Besides bulk and industrial oil, SMART’s refined products are also marketed under several brands such as Filma and Kunci Mas. Today, these brands have been recognised for their high quality and command significant market share in their respective segment in Indonesia.

Founded in 1962, SMART was listed on the Indonesia Stock Exchange in 1992 and is based in Jakarta. A subsidiary of Golden Agri-Resources (GAR), SMART has the oleochemical business, Sinarmas Oleochemical (PT SOCI MAS) and the SMART Research Institute (SMARTRI) within its operations.

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