Data Architecture & Governance Manager - Global Employer Services Technology

This role focuses on defining and managing data architecture, data modeling, governance, and operations within a global employer services technology group. The manager will oversee the creation of target-state data architecture, enterprise data models, and governance practices to improve data quality and compliance. Responsibilities include defining data platforms, establishing governance frameworks, partnering with stakeholders, enforcing architecture principles, driving master data strategies, overseeing data quality management, guiding tooling selection, ensuring regulatory compliance, and managing a team of data professionals.

What you'd actually do

  1. Define and maintain the enterprise data architecture, data models, standards, and roadmap aligned to business and analytics priorities.
  2. Lead the design of scalable, secure, and modern data platforms, including data lakes, warehouses, semantic layers, and integration patterns.
  3. Establish and operationalize data governance frameworks covering data ownership, stewardship, metadata, lineage, quality, privacy, retention, and access controls.
  4. Partner with business, engineering, security, and analytics leaders to prioritize data domains and enable trusted, high-value data products.
  5. Create and enforce architecture principles, reference models, and design standards for structured and unstructured data.

Skills

Required

  • data architecture
  • data management
  • enterprise data leadership
  • master data management (MDM)
  • data governance
  • metadata management
  • data quality
  • data modeling
  • data standards
  • Informatica (MDM, 360, Data Catalog)
  • Reltio (Multi-domain MDM, Intelligent 360, advanced data models)
  • cloud-based data lakes
  • warehouse technologies (Apache Iceberg, Databricks, Redshift, Snowflake)
  • data products
  • data catalogs
  • data marketplaces
  • semantic layers for analytics
  • agentic AI use cases
  • leading workstreams
  • distributed teams
  • cross-functional workshops

Nice to have

  • Generative AI
  • advanced data architectures
  • Data Mesh
  • Data Fabric
  • Data Products
  • data modeling techniques
  • entity-relationship
  • star/snowflake schemas
  • 3rd normal form
  • medallion data architecture (bronze, silver, gold)
  • cloud-based data lakes
  • warehouse technologies (Apache Iceberg, Databricks, Redshift, Snowflake)
  • data integration (ETL/ELT)
  • data quality frameworks

What the JD emphasized

  • data architecture
  • data modeling
  • data governance
  • data quality
  • data management
  • regulatory requirements
  • privacy requirements
  • data security policies
  • regulatory requirements