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Job Posting Location
Bangkok
Job Summary
Data quality, metadata management, data lineage and data governance.
Job Description
Key Responsibilities:
- Design and implement frameworks for data quality validation, including rules, thresholds, and metrics to ensure high-quality data.
- Automate data quality monitoring and anomaly detection using tools or custom scripts.
- Collaborate with data stewards to resolve data quality issues and improve processes.
- Develop and maintain centralized metadata repositories to ensure accurate and up-to-date metadata.
- Automate metadata extraction, data lineage tracking, and validation processes.
- Integrate metadata management solutions with tools like Informatica EDC, Axon, or similar platforms.
- Work closely with the Data Governance team to implement data governance policies and data standards across the data lifecycle.
- Create and maintain pipelines to enable data lineage, audit trails, and compliance reporting.
- Support the adoption of governance tools and frameworks to ensure consistent data usage.
- Build robust, scalable, and secure ETL/ELT pipelines for structured and unstructured data.
- Optimize data ingestion, transformation, and storage for hybrid (on-premises and on cloud) environments.
- Ensure data pipeline reliability and performance through monitoring and testing.
- Work closely with data stewards, data analysts, and data governance teams to align engineering efforts with business needs.
- Mentor junior team members on best practices in data engineering and governance.
Required Qualifications:
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Experience:
5-10 years of experience in data engineering, with a focus on data quality, metadata, data lineage and data governance. -
Technical Skills:
- Strong programming skills in Python, SQL, or Scala; experience with modern data frameworks such as PySpark and dbt (Data Build Tool) is a plus.
- Expertise in ETL/ELT tools like Informatica Intelligent Data Management Cloud (IDMC), Talend, Apache NiFi, or similar cloud-native solutions.
- Proficiency with metadata management platforms such as Informatica EDC, Collibra, or Alation, including automation of metadata ingestion, classification, and lineage mapping.
- Hands-on experience with data quality tools (e.g., Informatica Data Engineering Quality (DEQ), Collibra Data Quality & Observability, Great Expectations) and custom validation scripting.
- Strong knowledge of data governance frameworks and tools (e.g., Informatica Axon, Collibra Governance, Alation Data Governance).
- Experience with cloud data platforms and databases (e.g., Snowflake, Databricks, Oracle, SQL Server), as well as data lake/lakehouse architectures.
- Familiarity with multi-cloud and hybrid environments (e.g., AWS, Azure, Google Cloud Platform) and their native data services.
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Practical experience applying Generative AI and Large Language Models (LLMs) for:
- Metadata automation (auto-tagging, semantic enrichment, and data catalog population)
- Anomaly detection in pipelines and datasets using AI-driven observability tools
- Data quality improvement through AI-based rules generation, pattern recognition, and automated remediation suggestions
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Soft Skills:
- Strong problem-solving and analytical abilities.
- Excellent communication and collaboration skills.
- Ability to mentor and guide junior team members.
Preferred Qualifications:
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Certifications in relevant areas, such as:
- Data Governance: Certified Data Governance Professional (CDGP) or equivalent.
- Data Engineering: AWS Certified Data Analytics, Azure Data Engineer Associate, or Google Professional Data Engineer.
- Experience with Generative AI solutions for metadata and anomaly detection.
- Familiarity with agile methodologies and tools like Jira or Confluence.
Recruiter
Supaporn Limsiritong (สุภาภรณ์ ลิมศิริธง)