Posted at: 1 April

Senior Data Governance Analyst (Azure Purview + Data Engineering)

Company

CompanyData Meaning

Data Meaning is a leading Business Intelligence consulting firm headquartered in the US, specializing in Business Intelligence, Data Warehousing, and Project Management for a global B2B market.

Remote Hiring Policy:

Data Meaning is a fully remote company with team members across 13 states and 6 countries, hiring from various locations globally.

Job Type

Full-time

Allowed Applicant Locations

Brazil

Job Description

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