✨ Your talent drives our future

Getnet is a global technology company specializing in payment solutions for commerce. Founded in Brazil and operating across Latin America and the Iberian Peninsula, we support over 1.3 million merchants with end-to-end services — from POS terminals to e-commerce platforms.

We are part of PagoNxt, the global fintech of the Santander Group, and operate as an acquiring hub with a strong presence in Spain, Portugal, Brazil, Mexico, Chile, Argentina, and Uruguay.

Our mission is clear: to simplify payments with innovation, security, and scale, helping businesses of all sizes grow with agility.

We offer a unified platform that integrates hardware, software, fraud prevention, acquiring, reconciliation, and financial services — all in a single ecosystem, so our clients can focus on growing their business.

Being part of Getnet means joining a company that combines the innovation of a fintech with the solidity of a global bank.

Imagine your future. Care for your career. Simplify your journey.

This means you'll have the chance to build impactful solutions, grow with real development opportunities, and thrive in a culture that values well-being, inclusion, and clarity.

We combine flexibility, autonomy, and global collaboration — so you can focus on what matters, connect with purpose, and help shape the future.

Here, you'll find space to grow, real opportunities to lead, and a culture where everyone belongs and contributes.

✨ If you want to be part of the next generation of financial solutions, this is the place.

Define, govern, and ensure the end-to-end architecture for data ingestion and preparation supporting the Common Semantic Layer (CSL), ensuring alignment between technical ingestion, semantic modeling, and external provider requirements.

📌 What you'll do

Define and evolve the data ingestion and preparation architecture for CSL
Ensure alignment between:

Technical ingestion pipelines
Semantic data model (CSL)
External provider data dictionary and mappings

Create, validate, and enforce architecture standards for data ingestion and transformation
Act as a bridge between engineering teams, external providers, and business stakeholders
Ensure consistency across Stage, Common, and Refined layers
Define ingestion strategies by country and data source
Identify and mitigate structural risks, including:

External data dependencies (e.g., NUEK)
Undefined or unavailable data sources
Mapping misalignment

Govern data mappings, transformation rules, and standardization
Disseminate best practices in data architecture and governance
Provide technical guidance to analysts (Senior IT Analysts)
Ensure full documentation, including:

AS-IS / TO-BE architectures
Data models
Ingestion flows
Transformation rules

Manage dependencies, risks, and deliverables with close project oversight

📌Technical Skills

Strong experience in:

Data architecture (Data Lake / Lakehouse)
Event-driven and service-oriented architectures (EDA / SOA)
Data integration platforms (ADF, Databricks, etc.

Experience in cloud environments (preferably Azure)
Strong data modeling skills (conceptual, logical, semantic)
Experience with data governance frameworks (e.g., DAMA, TOGAF)
Knowledge of observability (logging, tracing, monitoring)

📌Requirements

Education

Degree in Engineering, Computer Science, Telecommunications, Mathematics, or equivalent.

Experience

8–10 years of experience in data‑related roles within the Santander Group, leading both technical and functional teams.
Experience within PagoNxt will be highly valued.
Experience with federated and domain‑oriented data architectures.
Experience with Data Lakes and platforms based on Databricks.
Experience in data governance: cataloging, quality, lineage, MDM, standards, etc.
Experience managing backlogs and applying Agile methodology.
Strong command of Jira and Confluence.
Experience with cloud environments (AWS/Azure/GCP).
Knowledge of data security and access control models.
Experience defining Data Governance frameworks from scratch or scaling them globally.
Experience implementing or managing tools such as Openmetada or other data governance tools.
Experience defining data quality metrics and monitoring frameworks.
Experience driving adoption of enterprise data platforms.