Data Steward

Ex; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Ex in the United States seeks an experienced data governance leader to strengthen data ownership, standardize metadata, and ensure compliant data access across the organization.

You will drive end-to-end data lineage, classification of sensitive data, and collaboration with Data Modelers, Data Engineers, and Product teams on data contracts and modernization efforts across AWS and Databricks.

Qualifications

• 7+ years of experience in data governance, data stewardship, data quality, or data management.
• Strong knowledge of metadata, lineage, data classification, access governance, and privacy.
• Proven experience defining, implementing, and monitoring data quality rules, controls, KPIs, and remediation processes, including data profiling and root cause analysis.
• Experience with data contracts, schema governance, data-quality SLAs, change management processes.
• Working knowledge of SQL and modern enterprise data platforms, including cloud-based data lakes, warehouses, and analytics ecosystems.
• Experience with catalog/governance tools like Databricks Unity Catalog, Collibra, Alation, or Informatica.
• Strong communication, facilitation, and stakeholder management skills, with the ability to engage effectively with business, technical, risk, privacy, and executive stakeholders.

Responsibilities

• Define and maintain data ownership, glossaries, and metadata standards across enterprise data domains.
• Establish and monitor data quality rules, controls, and thresholds; coordinate remediation with Data Engineering.
• Classify PII, confidential, and sensitive data assets with documented access controls, privacy requirements, retention policies, and usage guidelines.
• Document end-to-end data lineage across source systems, data pipelines, and analytical products.
• Support governance activities for data modernization, including migrations to AWS and Databricks environments.
• Facilitate cross-functional governance forums to align data definitions, ownership, and quality issues.
• Develop governance policies, standards, processes, metrics, and reporting for consistent data management.
• Define governance requirements for data contracts, including ownership, data quality, lineage, and usage.
• Partner with Data Modelers, Data Engineers, and Data Product teams on contract lifecycle, schema evolution, and change management.
• Drive adoption of governance best practices and accountability for data stewardship.

Skills

Data governance

Data stewardship

Data quality

Metadata

Data lineage

Access governance

Privacy

Data contracts

Change management

SQL

Tools

Databricks Unity Catalog

Collibra

Alation

Informatica

Job description

This role will collaborate closely with Business, Data Product, Engineering, Privacy, and Cybersecurity teams to strengthen data ownership, standardize business definitions, improve data quality, manage data classification and lineage, and ensure effective data access governance and compliance.

Responsibilities

• Define and maintain data ownership, business glossaries, critical data elements (CDEs), data dictionaries, and metadata standards across enterprise data domains.
• Establish and monitor data quality rules, controls, and thresholds; identify data issues and coordinate remediation efforts with Data Engineering teams.
• Classify PII, confidential, and sensitive data assets, ensuring appropriate documentation of access controls, privacy requirements, retention policies, and approved usage guidelines.
• Document and maintain end-to-end business and technical data lineage across source systems, data pipelines, and analytical data products.
• Support governance activities for data modernization initiatives, including migration from legacy platforms to AWS and Databricks environments.
• Facilitate cross-functional governance forums, driving alignment and resolution of data definition, ownership, and quality issues across business and technology teams.
• Develop and implement governance policies, standards, processes, documentation, metrics, and reporting to promote consistent data management practices.
• Define and enforce governance requirements for data contracts, including ownership, business definitions, data quality expectations, sensitivity classifications, lineage, and approved usage.
• Partner with Data Modelers, Data Engineers, and Data Product teams to manage data contract lifecycle activities, including schema evolution, versioning, change management, and producer-consumer accountability.
• Drive adoption of data governance best practices and foster accountability for data stewardship across business and technical stakeholder groups.

Qualifications

Qualifications (Required):

• 7+ years of experience in data governance, data stewardship, data quality, or data management.
• Strong knowledge of metadata, lineage, data classification, access governance, and privacy.
• Proven experience defining, implementing, and monitoring data quality rules, controls, KPIs, and remediation processes, including data profiling and root cause analysis.
• Experience with data contracts, schema governance, data-quality SLAs, change management processes.
• Working knowledge of SQL and modern enterprise data platforms, including cloud-based data lakes, warehouses, and analytics ecosystems.
• Experience with catalog/governance tools like Databricks Unity Catalog, Collibra, Alation, or Informatica.
• Strong communication, facilitation, and stakeholder management skills, with the ability to engage effectively with business, technical, risk, privacy, and executive stakeholders.

Ability to help shape a governance operating model, not only execute established processes.

Preferred Experience:

• Experience with modern data platforms and cloud technologies, including Databricks, Unity Catalog, Delta Lake, and AWS.
• Domain expertise in media, streaming, advertising, subscription, audience, customer, or consumer data environments.
• Experience supporting large-scale data modernization and migration initiatives, including transitions from legacy platforms to cloud-based architectures.