Overview

Data Governance Analyst Jobs in Federal Territory of Kuala Lumpur, Malaysia at E-Outsource Asia

Title: Data Governance Analyst

Company: E-Outsource Asia

Location: Federal Territory of Kuala Lumpur, Malaysia

Responsibilities

  • Define, maintain and version data standards, definitions and business glossary for in‑scope domains; deliver a single-source-of-truth catalogue entry for each CDE.
  • Document Critical Data Elements (CDEs) with classification (sensitivity/confidentiality), lineage, acceptable values, usage rules and retention.
  • Deliverable: CDEs documented for X domains within Y weeks (to be agreed at onboarding).
  • Design, implement and maintain data quality rules, scorecards and a versioned rules catalogue for critical data elements (DCEs) in alignment with governance policies.
  • Perform data profiling, statistical analysis and anomaly detection to surface and prioritize issues; perform root‑cause analysis and coordinate remediation.
  • Embed automated checks and validations into ETL/ELT pipelines (Databricks/Spark or equivalent) to enable continuous testing and end‑to‑end lineage of quality metrics.
  • Facilitate the data ownership/stewardship model. Establish and publish roles, responsibilities, decision rights, and escalation paths. Deliverable: steward RACI and escalation matrix within first 6 weeks.
  • Translate governance policies into technical and operational rules together with Data Engineers (naming conventions, modelling guidelines, access controls).
  • Deliverable: implementable rule set and sample automated checks for priority datasets within 3 months.
  • Manage the metadata repository/data catalogue: ensure discoverability, lineage, and business context for sources and transformations.
  • Configure, integrate and operate data quality tooling (e.g., Great Expectations, Deequ, Databricks native checks, Microsoft Purview, or approved DQ tools), including dashboards, alerts and SLA monitoring.
  • Triage and coordinate remediation of data issues: maintain issue logs, lead RCA workshops, assign actions, and track SLAs to closure. Deliverable: weekly exception reports and SLA dashboard.
  • Define and monitor data governance and quality KPIs (completeness, accuracy, timeliness, uniqueness, policy adherence); agree baseline targets during onboarding and provide monthly dashboards.
  • Define and socialize target thresholds, exception handling and remediation workflows; own the exceptions queue until closure and verify fixes.
  • Apply CI/CD best practices for quality rules and tests; maintain automation to prevent regressions.
  • Support data access governance and privacy: participate in access reviews, assist
  • Legal/Compliance on regulatory requests and ensure controls meet policy (GDPR/CCPA as applicable).
  • Create and run training, playbooks, onboarding kits for stewards and data consumers; recommend and help implement automation (catalogue integrations, alerting).
  • Act as liaison across business, analytics, engineering and compliance to balancerisk mitigation and business enablement.
  • Work with procurement and vendor teams on tool selection, SOW review and vendor onboarding when external solutions or services are proposed.
  • Evangelize DQ best practices, contribute to governance standards, and provide training/handovers to data stewards.

Profile

  • Bachelor’s degree in Information Systems, Computer Science, Data Management,or related field (or equivalent experience).
  • 3–5+ years in data governance, data management, data quality or related roles.
  • Practical experience with metadata/catalogue tools and data-quality frameworks.
  • Strong SQL skills and proficiency in one or more programming languages used for data work (Python preferred; Scala/Java acceptable).
  • Familiarity with privacy/regulatory frameworks (e.g., GDPR, CCPA) and data access controls.
  • Strong stakeholder management, facilitation, and written/verbal communication skills.
  • Ability to work with engineering teams to implement technical controls.
  • Hands‑on experience with Databricks/Spark or equivalent big data platforms.
  • Practical experience implementing DQ frameworks or tools (e.g., GreatExpectations, Deequ, Informatica DQ, Talend, or native Databricks checks)
  • Experience with data catalogue/lineage tools (e.g., Microsoft Purview, Alation)and familiarity with metadata management concepts.
  • Experience with cloud platforms (Azure, AWS or GCP) and storage formats (DeltaLake, Parquet).
  • Experience with observability/monitoring tools (Grafana, Datadog, Prometheus).
  • Certifications (Databricks, Azure Data Engineer, CDMP) or experience with data privacy and regulatory controls (GDPR/CCPA).
  • Prior experience working with third‑party vendors, drafting SOWs, or managing outsourced DQ implementations.
  • Familiarity with agile delivery, CI/CD tooling, and automated testing frameworks.
  • Fluent English and Mandarin to communicate with client teams based in China and Hong Kong.

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