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āļāļąāļāļĐāļ°:
Microsoft Office, Power point
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļŠāļāļąāļāļŠāļāļļāļāļāļēāļĢāļāļąāļāļāļģāļāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđ āļĢāļēāļĒāļāļēāļ āđāļĨāļ°āđāļāļāļŠāļēāļĢāļāđāļēāļ āđ āļāļāļāļāđāļēāļĒāļ§āļīāđāļāļĢāļēāļ°āļŦāđ.
- āļŠāļāļąāļāļŠāļāļļāļāļāļēāļĢāļāļąāļāļāļīāļāļāļĢāļĢāļĄ āđāļāđāļ Company Visit, Analyst Meeting, Conference āđāļĨāļ°āļāļēāļ Investor Relations.
- āļāļąāļāđāļāļĢāļĩāļĒāļĄ Presentation āđāļāļāļŠāļēāļĢāļāļĢāļ°āļāļāļāļāļēāļĢāļāļĢāļ°āļāļļāļĄ āļŠāļąāļĄāļĄāļāļē āđāļĨāļ°āļāļīāļāļāļĢāļĢāļĄāļāļāļāļāđāļēāļĒāļ§āļīāđāļāļĢāļēāļ°āļŦāđ.
- āļāļđāđāļĨāļāļēāļĢāđāļāļĒāđāļāļĢāđāļāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļāđāļāļĄāļđāļĨāļāđāļēāļāļāđāļāļāļāļēāļāļāđāļēāļ āđ āļāļāļāļāļĢāļīāļĐāļąāļ.
- āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāļāļēāļāļāđāļāļĄāļđāļĨ āļāļēāļāđāļāļāļŠāļēāļĢ āđāļĨāļ°āļāļēāļāļāļļāļĢāļāļēāļĢāļāļāļāļāđāļēāļĒāļ§āļīāđāļāļĢāļēāļ°āļŦāđ.
- āļāļĢāļ§āļāļŠāļāļāļāļ§āļēāļĄāļāļđāļāļāđāļāļāļāļāļāļāđāļāļĄāļđāļĨ āđāļāļāļŠāļēāļĢ āđāļĨāļ°āļĢāļđāļāđāļāļāļĢāļēāļĒāļāļēāļāļāđāļāļāđāļāļĒāđāļāļĢāđ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĢāļīāļĐāļąāļāļāļāļāļ°āđāļāļĩāļĒāļ āļŦāļāđāļ§āļĒāļāļēāļāļ āļēāļĒāđāļ āđāļĨāļ°āļĨāļđāļāļāđāļēāļŠāļāļēāļāļąāļāļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ.
- āļ§āļļāļāļīāļāļĢāļīāļāļāļēāļāļĢāļĩāļāđāļēāļāļāļēāļĢāđāļāļīāļ āđāļĻāļĢāļĐāļāļĻāļēāļŠāļāļĢāđ āļāļąāļāļāļĩ āļāļĢāļīāļŦāļēāļĢāļāļļāļĢāļāļīāļ.
- āļĄāļĩāļāļ§āļēāļĄāļĨāļ°āđāļāļĩāļĒāļāļĢāļāļāļāļāļ āļĢāļąāļāļāļīāļāļāļāļāļŠāļđāļ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļāļāļąāļāļĨāļģāļāļąāļāļāļ§āļēāļĄāļŠāļģāļāļąāļāļāļāļāļāļēāļāđāļāđāļāļĩ.
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāļāļĢāļ°āļŠāļēāļāļāļēāļāđāļĨāļ°āļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢāļāļĩāđāļāļĩ āļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļĢāđāļ§āļĄāļāļąāļāļŦāļĨāļēāļĒāļāđāļēāļĒāđāļāđāļāļĒāđāļēāļāļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļ.
- āļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļ āļēāļĒāđāļāđāđāļĢāļāļāļāļāļąāļāđāļĨāļ°āļāļĢāļīāļŦāļēāļĢāļŦāļĨāļēāļĒāļāļēāļ (Multi-tasking) āļāļĢāđāļāļĄāļāļąāļāđāļāđ.
- āļĄāļĩāļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāđāļāđ Microsoft Office āđāļāļĒāđāļāļāļēāļ° Excel, PowerPoint āđāļĨāļ° Word āđāļāļĢāļ°āļāļąāļāļāļĩ.
- āļĄāļĩāļāļąāļāļĐāļ°āļ āļēāļĐāļēāļāļąāļāļāļĪāļĐāđāļāļĢāļ°āļāļąāļāļāļĩāđāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļāļģāļāļ§āļēāļĄāđāļāđāļēāđāļāđāļāļāļŠāļēāļĢāļāļēāļāļāļļāļĢāļāļīāļāļŦāļĢāļ·āļāļāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļāđ.
- āļĄāļĩāļāļ§āļēāļĄāļāļĢāļ°āļāļ·āļāļĢāļ·āļāļĢāđāļāđāļāļāļēāļĢāđāļĢāļĩāļĒāļāļĢāļđāđāļŠāļīāđāļāđāļŦāļĄāđ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļāļāļĢāļąāļāļāļąāļ§āļāļąāļāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāđāļāđāļāļĩ.
- āļŠāļēāļĄāļēāļĢāļāļĢāļąāļāļĐāļēāļāļ§āļēāļĄāļĨāļąāļāļāļāļāļāđāļāļĄāļđāļĨāļāļĢāļīāļĐāļąāļāđāļĨāļ°āļĨāļđāļāļāđāļēāđāļāđāđāļāđāļāļāļĒāđāļēāļāļāļĩ.
- āļĄāļĩāđāļāļĢāļąāļāļāļēāļāļāļĢāļīāļāļēāļĢ (Service Mind) āļāļĢāđāļāļĄāļŠāļāļąāļāļŠāļāļļāļāļāļēāļĢāļāļģāļāļēāļāļāļāļāļāļĩāļĄāļāļąāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļŦāļāđāļ§āļĒāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
āļāļąāļāļĐāļ°:
Microsoft Office, Power point
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
āļŦāļāđāļēāļāļĩāđāļŦāļĨāļąāļāđāļāļŦāļāđāļ§āļĒāļāļēāļ - āļ§āļīāđāļāļĢāļēāļ°āļŦāđ āļāļāļāđāļāļ āđāļĨāļ°āđāļŦāđāļāļģāđāļāļ°āļāļģāđāļāļāļēāļĢāļāļąāļāļāļģ Workflow, Business Requirement āļāļĨāļāļāļāļāļāļēāļĢāļāļāļŠāļāļāļĢāļ°āļāļ (UAT) āļĢāļ°āļāļāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āđāļāļ·āđāļāļāļąāļāļāļēāļĢāļ°āļāļāļāļēāļāđāļŦāđāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļēāļĢāļāļāļīāļāļąāļāļīāļāļēāļ āļāđāļāļāļģāļŦāļāļāļāļēāļĄāļāļāļŦāļĄāļēāļĒ āļĢāļ§āļĄāļāļķāļāđāļāļāđāļāđāļĨāļĒāļĩāđāļŦāļĄāđāđ - āļāļĢāļ°āļŠāļēāļāļāļēāļāđāļĨāļ°āļāļģāđāļāļīāļāļāļēāļĢāđāļāđāđāļāļāļąāļāļŦāļēāļĢāļ°āļāļāļāļēāļāļĢāļąāļāļāļĢāļ°āļāļąāļ - āļāļģāđāļāļīāļāļāļēāļĢāļāļąāļāļāļģāļĢāļ°āļāļāļāļēāļāļŠāļāļąāļāļŠāļāļļāļāļāļ·āđāļāđ āļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ - āļĢāđāļ§āļĄāļāļģāđāļāļīāļāļāļēāļĢāđāļāđāļāļāļāļēāļ/āđāļāļĢāļāļāļēāļĢāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ āļāļēāļĢāļĻāļķāļāļĐāļē āļŠāļģāđāļĢāđāļāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļāļąāļāļāļĢāļīāļāļāļēāļāļĢāļĩāļāļķāđāļāđāļ āļŠāļēāļāļēāļāļĢāļ°āļāļąāļāļ āļąāļĒ/āļŠāļāļīāļāļī/āđāļāļāđāļāđāļĨāļĒāļĩāļŠāļēāļĢāļŠāļāđāļāļĻ āļāļļāļāļŠāļĄāļāļąāļāļī - āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđ āļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨ āļ§āļēāļāđāļāļāļāļĩāđāļāļĩ - āļĄāļĩāļāļ§āļēāļĄāļĢāļąāļāļāļīāļāļāļāļāļāđāļāļŦāļāđāļēāļāļĩāđ āļĨāļ°āđāļāļĩāļĒāļāļĢāļāļāļāļāļ āļĄāļĩāđāļŦāļ§āļāļĢāļīāļāļāļāļīāļ āļēāļ āļĄāļĩāļāļ§āļēāļĄāļŠāļēāļĄāļē ...
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Risk Management, English, Thai
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Produce in-depth analysis of the Thai economy, policy environment, and external conditions, with clear views and well-reasoned scenarios that inform bank decision-making.
- Deliver macroeconomic, interest rate, and FX outlook analysis to support ALCO decisions on balance sheet positioning, funding strategy, and market risk.
- Monitor and interpret financial market developments Thai government bond yields, THB and regional FX dynamics, policy rate path, and global rates and translate them int ...
- Contribute macroeconomic inputs to stress testing, ICAAP, and other regulatory and internal risk exercises, and assess credit cycle and sector conditions to inform credit policy and business direction.
- Provide macro and rates/FX views to support capital markets activity across fixed income and FX trading, DCM origination, and structured product pricing.
- Maintain a working Thai macro forecast framework and the databases needed to track macroeconomic, financial market, and banking sector indicators.
- Present research findings clearly and confidently to ALCO, senior management, and other internal committees in written reports and verbal briefings and collaborate closely with treasury, risk, credit, and capital markets teams to embed economic insights into bank strategy.
- Track record of producing high-quality macroeconomic analysis on Thailand or regional economies.
- Prior experience at a commercial or central bank, with exposure to ALCO frameworks, stress testing, and bank risk management practices.
- Familiarity with Thai monetary policy frameworks, banking operations, and the domestic regulatory environment.
- Familiarity with capital markets activity equity market, fixed income, FX, and derivatives markets and the macro drivers of trading and origination flow.
- Understanding of loan and credit processes, sector credit analysis, and the drivers of bank asset quality through the cycle.
- Prior team leadership or mentoring of junior analysts.
- Advanced degree in Economics, Finance, or a closely related quantitative discipline strongly preferred.
- Strong foundation in economics, finance, and data analytics.
- Proven ability to produce consistent, logically structured, evidence-based analysis under time pressure.
- Quantitative literacy comfort with time series data, econometric techniques, and statistical reasoning as tools to support analysis.
- Strong collaborative instincts and ability to work effectively across research, treasury, risk, capital markets, and business teams.
- Strong written and verbal communication skills in both Thai and English.
- Specific knowledge and skill / āļāļ§āļēāļĄāļĢāļđāđāđāļāļāļēāļ°āļāļģāđāļŦāļāđāļ.
- Apply now ".
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Problem Solving, Architecture, Automation, Big Data, Python, Apache, Kafka, Scala, SQL, ETL
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- We are looking for a visionary and technical.
- Lead Data Engineer.
- to guide and scale our data engineering team within our regional data chapter. In this role, you will own the architecture, evolution, and reliability of our next-generation regional data platform. You will lead a talented team of engineers to optimize our.
- Databricks-driven Data Lakehouse architecture., drive core DataOps practices, implement robust data governance, and collaborate across functional squads to empower advanced analytics, business intelligence, and AI initiatives.
- The ideal candidate is an expert data architect and a proven technical leader who thrives on transforming messy, disconnected datasets into a unified, low-latency, and highly secure data ecosystem.
- Design, build, and continuously optimize our scalable Data Lakehouse platform leveraging Databricks and AWS infrastructure to support global business expansion.
- Lead the design and implementation of highly automated, optimal real-time and batch data extraction, transformation, and loading (ETL/ELT) frameworks. Oversee complex integration with internal microservices, external insurance partners, and third-party APIs.
- Champion engineering best practices by building framework controls, schema registries, automated testing, and CI/CD pipelines for data assets (utilizing tools like dbt and Airflow). Drive initiatives like Databricks serverless migrations and automated performance monitoring.
- Own the end-to-end framework for regional data quality, data observability (e.g., Elementary), data freshness, and data catalogs. Ensure robust data security, compliance (PDPA), and sensitivity tagging across multi-region boundaries.
- Partner with Executives, Product Owners, Software Developers, Data Analysts, and MLOps/Data Science squads to unblock complex technical dependencies, align infrastructure capabilities, and deliver actionable data products.
- Actively research and spearhead proof-of-concepts incorporating advanced technologies like Generative AI/Agentic AI data pipelines (e.g., automated knowledge bases, smart web scraping solutions) into the data ecosystem.
- Manage, mentor, and elevate the technical capabilities of junior and senior data engineers within regional squads, ensuring standardized practices and strong technical ownership.
- 5+ years of experience in Data Engineering, Data Architecture, or a related technical capability role, with at least 2+ years leading engineering teams or core technical projects.
- Deep hands-on experience designing and managing production workloads in.
- Databricks.
- (Delta Lake, Unity Catalog, and serverless compute paradigms).
- Master-level proficiency in.
- SQL.
- (complex query authoring, optimization, and macro writing) and programmatic data engineering in.
- Python.
- or.
- Scala.
- Heavy experience with Big Data open-source frameworks, primarily.
- Apache Spark.
- Expertise with modern cloud data pipeline orchestration tools (e.g.,.
- Airflow., Dagster) and transformation tools like.
- dbt.
- Solid mastery over.
- AWS cloud services.
- infrastructure (S3, EC2, RDS, VPC configurations, network connectivity) integrated within data ecosystems.
- Expert knowledge of transactional databases, distributed storage, message queuing/streaming (e.g., Kafka), and structural patterns for Lakehouse data modeling (Medallion architecture: Bronze, Silver, Gold layers).
- Proven experience performing root cause analysis on production infrastructure failures, handling complex code/infrastructure migrations, and managing data pipeline debts (e.g., optimizing small file storage).
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or a highly quantitative relevant field.
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āļĒāļāļāļāļīāļĒāļĄ
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