Data Engineer – Finance Technology (AI & Data Intelligence)

About the role

Visa is building a next‑generation data intelligence and AI platform for Finance. As a Data Engineer in the Finance Technology – Data Intelligence team, you will design and operate scalable data pipelines, semantic models, and AI‑enabled analytics solutions that drive smarter decision‑making across the organization.

Key responsibilities

• Architect and implement batch and streaming data pipelines (SQL, Hive, PySpark) across lake/lakehouse environments to create governed finance domain marts.
• Design dimensional and semantic models for self‑service analytics using Power BI, Fabric semantic models, and SSAS Tabular with DAX measures and row‑level security.
• Operationalize Gen AI capabilities (retrieval‑augmented generation, prompt‑chaining, agents) on regulated datasets, ensuring PII/SOX compliance.
• Collaborate with data analysts, data scientists, and software engineers to deliver secure, auditable, and reusable data and AI services.
• Implement CI/CD pipelines (Git, Azure DevOps/GitHub Actions), data quality testing (Great Expectations), and model deployment automation (MLflow, Azure ML, Fabric).
• Define observability metrics (lineage, drift, freshness, cost) and drive continuous performance tuning and cost optimisation.
• Produce high‑impact dashboards and scorecards in Power BI/Tableau for finance stakeholders.

Required profile

• Strong collaborative mindset with experience working alongside analysts, data scientists, and engineering partners.
• Demonstrated ability to build secure, reliable, and governed data solutions at scale.
• Experience delivering production‑grade AI/Gen AI features on sensitive data.
• Proven track record of implementing CI/CD and observability for data pipelines.

Required skills

• SQL, Hive, PySpark
• Power BI, Fabric semantic models, SSAS Tabular, DAX
• Azure DevOps, GitHub Actions, Git
• Great Expectations (or equivalent) for data quality testing
• MLflow, Azure ML, Fabric for model deployment
• Vector store concepts and retrieval‑augmented generation techniques
• Understanding of PII/SOX governance and data security controls