Data Engineering Senior Associate 1
Wha · สมุทรปราการ, Thailand
Weak hiring record · median 633 days open
All reasons
- Open 629 days
- 93% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
Overall Governance
- Ensure Compliance with Data Policies – Understand and apply data management policies, security standards, and governance frameworks in daily operations to ensure compliance with legal and regulatory requirements.
- Promote Ethical Data Use – Ensure the ethical and responsible use of data, adhering to relevant guidelines, privacy regulations (e.g., GDPR, PDPA), and corporate governance policies to maintain trust and transparency.
- Support Policy Revisions – Lead the periodic review and revision of data engineering policies, standards, and procedures to align with business objectives and improve efficiency.
Functional-related Accountabilities
- Stakeholder Coordination – Collaborate with business leaders, IT teams, and other stakeholders to identify opportunities for data-driven improvements, process automation, and AI integration.
- Data Management – Identify, validate, and manage structured and unstructured data sources, ensuring data integrity, accuracy, and quality for analysis and business applications.
- Data Pipeline Development – Design, build, and maintain scalable, secure, and reliable data pipelines that support analytics, reporting, and AI-driven decision-making.
- Data Transformation and Integration – Implement ETL/ELT processes to pre-process, transform, and integrate large datasets from various internal and external sources.
- Performance Optimization – Enhance data pipeline performance using indexing, caching, and partitioning techniques, ensuring efficient data processing and fast query execution.
- RPA & Automation – Utilize UiPath RPA and other automation tools to optimize data workflows, reduce manual tasks, and enhance operational efficiency.
- Documentation and Reporting – Maintain clear and comprehensive technical documentation, data lineage reports, and operational guidelines to ensure transparency and accessibility.
- Continuous Learning – Stay updated on emerging data engineering technologies, AI-driven analytics, cloud innovations, and automation best practices, and recommend their adoption where beneficial.
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