Star Energy Geothermal is looking for a Senior Data Engineer to support our enterprise data transformation journey. This role will be responsible for designing, governing, and enabling a scalable, trusted, and business-aligned data ecosystem across multiple business domains, including operations, production, drilling, engineering, finance, HR, supply chain, and corporate functions.
As part of Indonesia's leading geothermal energy producer, this role will contribute to strengthening data-driven decision-making, enterprise reporting, advanced analytics, digital transformation, and future AI-enabled capabilities across the organization.
Key Responsibilities
- Define and develop the target-state enterprise data architecture across business domains, systems, data platforms, analytics, and reporting layers.
- Build a data transformation roadmap to convert fragmented, multi-source data into governed, scalable, and reusable enterprise data assets.
- Establish source-of-truth models, master data, reference data, data definitions, KPI logic, and business ownership for critical data domains.
- Design and oversee data ingestion, ETL/ELT, batch, near-real-time, and integration patterns from SAP, operational systems, engineering data, spreadsheets, and external sources.
- Ensure data flows are structured across raw, cleansed, curated, and consumption-ready layers for reporting, dashboards, analytics, and AI use cases.
- Develop and strengthen metadata management, data catalog, data lineage, source-to-target mapping, data stewardship, and data quality standards.
- Partner with business leaders, process owners, Data Owners, Data Stewards, IT teams, vendors, and implementation partners to align data architecture with business transformation priorities.
- Review data models, integration designs, dashboard data foundations, platform changes, and vendor solutions to ensure alignment with enterprise architecture and governance standards.
- Identify opportunities to simplify, automate, standardize, and scale data processes across business functions.
- Support capability building by educating business users and project teams on data standards, governance expectations, and effective data usage.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Engineering, Software Engineering, or a related field.
- Master's degree is an advantage, especially for candidates with strong exposure to enterprise data architecture, analytics, or digital transformation.
- Minimum 8–10 years of progressive experience in data engineering, database development, ETL/ELT, data integration, and enterprise analytics support.
- Proven hands-on experience in designing, building, and optimizing scalable data pipelines and supporting enterprise data platforms.
- Strong experience in data modeling, source-of-truth design, data lake architecture, and enterprise data transformation programs.
- Solid understanding of enterprise data management, data governance, metadata, lineage, data quality, and cross-functional business process integration.
- Experience with SAP-integrated environments, operational systems, engineering data, reporting platforms, cloud data platforms, or analytics tools is preferred.
- Professional certifications in data engineering, cloud data platforms, databases, analytics tools, Microsoft Azure, Microsoft Fabric, SQL, Databricks, or equivalent are preferred.
- Strong analytical thinking, problem-solving ability, communication skills, and stakeholder management capability.
- Experience in energy, utilities, industrial operations, or organizations with complex multi-domain data landscapes is strongly preferred.
What You Will Contribute
- Enable faster and higher-quality executive decision-making through trusted, consistent, and accessible enterprise data.
- Accelerate digital and business transformation by turning fragmented data and manual reporting into a governed data foundation.
- Strengthen data governance, auditability, accountability, and security through clear ownership, metadata, lineage, quality controls, and access standards.
- Improve cross-functional visibility by connecting operational, financial, engineering, HR, and corporate data into integrated performance views.
- Support innovation and continuous improvement by enabling advanced analytics, AI initiatives, and scalable data products.
Who We Are Looking For
We are looking for a senior data professional who is not only technically strong, but also able to connect data architecture with business needs. The ideal candidate is structured, collaborative, analytical, and comfortable working across functions to turn complex data environments into reliable, reusable, and business-ready data assets.
Apply Now
If you are an experienced data engineering professional with strong expertise in enterprise data architecture, transformation, governance, and analytics enablement, we invite you to apply and contribute to building Star Energy's trusted, scalable, and AI-ready data ecosystem.
