Data Engineer- Data Science Platform

Visa•Foster City, CA

3d•Hybrid

About The Position

We are looking for a Data Engineer to join our Merchant Data Platform’s Data Science & Modeling team — the group building the next generation of AI‑powered merchant intelligence. This team is responsible for the core data and ML capabilities that power our merchant ecosystem, from data enrichment and quality to real‑time insights and generative‑AI experiences. What the Team Is Doing The Merchant Data Platform team owns the full lifecycle of merchant intelligence: Processing and modeling hundreds of millions of transactions each day, transforming raw behavioral data into powerful merchant‑level features and signals. Developing GenAI‑driven merchant data enrichment, including agents that reason over unstructured data (web, documents, support logs) to auto‑classify merchants and identify missing attributes. Why This Role Is Exciting This is not a standard data engineering role. It’s a chance to shape how AI understands merchants and powers every experience built on top of merchant data. You will work at the intersection of high‑performance data systems, machine learning, and applied GenAI. You will: Build ML‑ready datasets, features, and signals that directly feed merchant‑facing models. Collaborate with DS/ML teams on LLM fine‑tuning pipelines, embeddings, retrieval systems, and agent orchestration. Design systems that ensure data quality, lineage, monitoring, and trust for every downstream consumer. Partner with product and engineering to unlock merchant‑level intelligence that impacts growth, risk, operations, and customer experience. This is a high‑ownership environment with deep technical challenges: high throughput, real‑time data, multimodal signals, and novel AI applications that don’t have a playbook. What Candidates Can Expect Hard technical problems: streaming feature pipelines and large‑scale batch/real‑time computation. End‑to‑end exposure, from ingestion to model outputs to end‑user AI experiences. Opportunities to experiment with next‑generation LLMs, fast inference runtimes, and AI agents. A collaborative, mission‑driven team that values experimentation, craftsmanship, and measurable impact. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Requirements

Minimum of 6 months of work experience or a Bachelor's Degree
Bachelor's degree in Computer science, Machine Learning, Data Science or related field.
Strong experience coding in Python.
Skilled in SQL basic libraries for machine learning such as scikit-learn and Pandas, as well as Jupyter Notebook.

Nice To Haves

Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and Query Engines.
Relevant experiences in modeling techniques such as logistic regression, Naive Bayes, SVM, decision trees, natural language processing or neural networks.
Experience in cloud services (AWS preferable – Sage Maker, EMR, Glue).
Understand ML infrastructure concepts such as feature store, batch inference and model pipeline orchestration.

Responsibilities

Build ML‑ready datasets, features, and signals that directly feed merchant‑facing models.
Collaborate with DS/ML teams on LLM fine‑tuning pipelines, embeddings, retrieval systems, and agent orchestration.
Design systems that ensure data quality, lineage, monitoring, and trust for every downstream consumer.
Partner with product and engineering to unlock merchant‑level intelligence that impacts growth, risk, operations, and customer experience.