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Data Meaning

Leaders in Business Intelligence and Data Solutions.

Senior Data Governance Analyst (Azure Purview + Data Engineering)

Data AnalystData AnalystFull TimeRemoteSeniorTeam 51-200H1B No SponsorCompany SiteLinkedIn

Location

Brazil

Posted

69 days ago

Salary

0

Seniority

Senior

Job Description

Senior Data Governance Analyst (Azure Purview + Data Engineering)

Data Meaning

Senior Data Governance Analyst (Azure Purview + Data Engineering) Brazil-based | Full-Time CLT | Data & Governance Why This Role Matters At Data Meaning, we are seeing rapid growth in enterprise data governance initiatives on Azure, with Microsoft Purview at the center. We’re looking for a Senior Data Governance Consultant who can lead end-to-end Purview implementations, shape governance strategy, and partner directly with clients to turn data into a trusted, governed asset. This is not a support role — this is a client-facing leadership position where you will define how organizations manage, secure, operationalize, and engineer their data platforms. What You’ll Do: Lead Azure Purview Implementations - Architect and deliver end-to-end Microsoft Purview solutions across enterprise environments - Design and configure: - Data Map and scanning strategies - Metadata ingestion and classification frameworks - End-to-end data lineage (ADF, Databricks, Snowflake, Fabric) - Establish scalable patterns for cataloging, discovery, and governance automation Define Data Governance Strategy - Design and implement enterprise data governance operating models - Lead development of: - Business glossaries - Data ownership & stewardship frameworks - Data classification and sensitivity policies - Conduct governance maturity assessments and define transformation roadmaps Build & Integrate Data Pipelines - Design, develop, and maintain ETL/ELT pipelines using: - Azure Data Factory (ADF) - dbt (data build tool) - Build and orchestrate workflows in Databricks (Apache Spark) - Develop Alteryx workflows to enable self-service analytics and business-driven data prep - Ingest and manage structured and unstructured data in Azure Data Lake Storage (ADLS) - Ensure governance is embedded directly into pipelines (lineage, quality, classification) Data Modeling & Platform Architecture - Architect and optimize data models in: - Snowflake - Databricks / Delta Lake - Apply modeling techniques: - Dimensional modeling - Data Vault - Collaborate with analytics teams to define semantic layers and business logic in dbt - Ensure performance, scalability, and cost efficiency across platforms Partner with Clients & Stakeholders - Lead client workshops to align business and technical stakeholders - Translate business needs into governance frameworks and data architecture solutions - Advise leadership on data risk, compliance, and best practices - Present solutions to both technical and executive audiences Enable Data Quality, Trust & Compliance - Define and implement data quality frameworks and rules - Establish: - Data lineage tracking - Metadata management standards - Support regulatory initiatives (e.g., GDPR, HIPAA, CCPA) through: - Data classification - Access controls - Audit readiness - Ensure consistent, trusted, and governed data across platforms Engineering & Automation - Develop Python-based solutions for: - Workflow automation - API integrations - Data operations - Write and optimize complex SQL queries, views, and stored procedures - Monitor and optimize pipeline performance, including: - Logging - Alerting - Error handling - Troubleshoot and resolve data pipeline and platform issues Integrate Across the Azure Data Ecosystem - Align governance and engineering across: - Azure Data Factory (ADF) - Databricks / Unity Catalog - Azure Data Lake Storage (ADLS) - Snowflake - Partner with engineering teams to embed governance into data pipelines and architecture Collaboration & Documentation - Work closely with: - Data analysts - Data scientists - BI engineers - Document: - Data pipelines - Data models - Governance policies - Contribute to data catalogs and internal knowledge repositories - Participate in code reviews and mentor junior team members What We’re Looking For Required Experience - 7+ years in data, analytics, engineering, or data governance roles - 3+ years hands-on experience with Microsoft Purview - Proven experience leading data governance implementations or programs - Strong understanding of: - Data cataloging, lineage, and metadata management - Data governance frameworks and operating models - Experience in client-facing / consulting roles Technical Expertise - Deep experience with Microsoft Purview (Data Map, scanning, classification, lineage) - Strong experience with: - Azure Data Factory (ADF) - Azure Data Lake Storage (ADLS) - Snowflake - Databricks / Unity Catalog - Experience with: - dbt for transformations and modeling - Alteryx (preferred) - Strong SQL skills - Working knowledge of Python for automation and data engineering - Experience building and optimizing data pipelines and ETL/ELT processes Governance & Business Skills - Experience designing: - Data stewardship models - Business glossaries - Governance policies and standards - Ability to bridge business and technical stakeholders - Strong communication and workshop facilitation skills Preferred - Experience with additional governance tools (Collibra, Alation) - Familiarity with: - CI/CD pipelines, Git, and DataOps practices - Azure certifications (e.g., DP-203, Purview-related) - Experience in regulated industries - Familiarity with Microsoft Fabric What Success Looks Like in This Role - You can lead a Purview implementation from 0 → production - You can define both: - Governance strategy - Data engineering architecture - You are equally comfortable: - Running executive workshops - Designing scalable data pipelines - You help clients move from data chaos → governed, production-grade data platforms Why Join Data Meaning - Work on high-impact, enterprise Azure data transformations - Be part of a fast-growing governance practice - Collaborate across data engineering, analytics, and AI teams - Opportunity to shape both governance and modern data platform capabilities

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