Job Summary We are seeking an experienced and detail-oriented
Data Steward
to drive the execution of enterprise data governance and data quality initiatives. This role operates as an
independent contributor , responsible for ensuring that data assets are trusted, well-governed, and accessible across the organization.
The Data Steward will
own the governance, lineage, and quality of data assets across the full data lifecycle—from ERP source systems through RAW, consumable, and KPI layers. Leveraging
data.world
as the enterprise data catalog, this role will ensure strong metadata management, lineage transparency, and data discoverability.
A key focus of this role is to
establish a consistent, trusted semantic layer that supports analytics and AI use cases , ensuring data is clearly defined, standardized, and ready for downstream consumption. The role requires a balance of governance expertise and
hands-on technical capability (SQL and Python)
to validate data, enforce quality, and support metadata and lineage automation.
Preferred Experience
Hands-on experience with
data.world
or similar modern data catalog platforms.
Strong understanding of
data governance frameworks
(e.g., DAMA-DMBOK).
Experience managing
data lineage and quality across multi-layered architectures
(ERP, data lakes, transformation layers, KPI/reporting).
Experience supporting or building
semantic layers for BI and/or AI use cases.
Proficiency in




SQL and Python for data analysis, profiling, and automation of data quality checks.
Experience working with
APIs or programmatic interfaces
for metadata and catalog automation.
Familiarity with
modern data platforms
(Databricks, Redshift, Athena).
Experience with
data visualization tools
(e.g., Power BI).
Knowledge of
data privacy and regulatory standards
(e.g., GDPR, CCPA).
Qualifications
Bachelor’s degree in computer science, Information Systems, Data Science, or related field.
3+ years of experience in
data stewardship, data governance, or data quality roles.
Demonstrated experience working with
data catalogs, metadata management, and lineage.
Strong problem-solving skills with the ability to
work independently and manage moderately complex data challenges.
Excellent communication and stakeholder management skills, with the ability to
influence and drive adoption of governance practices.
Comfortable working
hands-on with data using SQL and Python
to validate data, enforce quality rules, and support governance processes.
What Success Looks Like
Trusted, well-documented data assets across
ERP → KPI pipeline
High adoption and effective use of
data.world
Consistent and governed
business definitions and semantic layer
Measurable improvements in
data quality KPIs
Reliable,
AI-ready datasets
supporting analytics and decision-making

📌 Data steward (Centro-Norte)
🏢 ThermoFisher Scientific
📍 Centro-Norte