Senior Analytical Engineer

Visa•San Francisco, CA

1d•Hybrid

About The Position

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world. Progress starts with you. We are seeking a forward-thinking and hands-on Senior Manager to lead our Analytics Engineering practice. In this high-impact role, you will act as the primary architect and lead developer for our analytics ecosystem. You will be responsible for migration of Cloud data and establishing Microsoft Fabric as our central analytics hub, and executing complex data pipelines. This is a technical leadership role for a builder. You will drive an AI-First methodology, leveraging AI coding assistants to accelerate development while designing data structures that power future AI Agents and LLMs. You will define the standards, write the core code, and own the technical roadmap. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Requirements

8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD
7+ years of Analytical Engineering experience.
Proven experience leading technical projects, architecture design, or migrations (formal people management experience is not required, but technical leadership is essential).
Core Stack: Mastery of Python/PySpark, SQL, and Airflow.
Legacy Stack: Expert familiarity with Bash, Unix, Hadoop, Hive, Trino, SSH, the terminal, and HDFS.
Cloud & Platforms: Strong experience with Microsoft Fabric, Azure, Databricks, Synapse, and/or AWS.
DevOps: Proficient in GitHub flows (Branching, Merging, Reverting), GitHub Actions, and Test-Driven Development (TDD).

Nice To Haves

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
Demonstrated interest or experience in Generative AI (specifically tools like Cline and/or Claude Code) for building data foundations or process automation.
Strong experience with context and prompt engineering, token management, and sub-agent management.
Ability to leverage AI tools to accelerate coding velocity and enforce coding standards.

Responsibilities

Architecture & AI Strategy:
Fabric Architecture: Design and implement the end-to-end Medallion Architecture (Bronze/Silver/Gold) within Microsoft Fabric, ensuring data is structured not just for BI reporting, but optimized for AI/ML integration.
Data for AI: Lead the strategy for building Data for AI pipelines—preparing unstructured text and data for vectorization, RAG (Retrieval-Augmented Generation), and AI Agent consumption.
AI-First Development: Champion the use of AI coding assistants (e.g., Copilot, Cline, Claude Code) to generate boilerplate code, write unit tests, and document logic, setting the standard for high-velocity development.
Migration & Pipeline Execution:
Hadoop Migration: Lead the technical strategy and execution of migrating on-prem Hadoop data to the Cloud (AWS/Azure) and connecting it to Fabric.
Complex Pipeline Development: Build and maintain complex PySpark notebooks and data flows. Orchestrate data movement between on-prem, cloud, and hybrid data systems, specifically sourcing information from CRM/ERP systems such as Microsoft Dynamics or Salesforce.
Legacy Integration: Utilize deep knowledge of Bash, Unix, and HDFS to interact with legacy systems during the migration phase.
DevOps, Standards & Project Management:
Code Quality & Governance: Act as the gatekeeper for the GitHub repository. Enforce strict CI/CD practices, manage branching strategies, and perform code reviews to ensure production-grade quality.
Project Leadership: Manage the engineering roadmap using tools like Jira or Jira Align. Translate high-level business requirements from stakeholders into technical sprints and deliverables.
Collaboration: Partner with the BI team to ensure Gold layer data models are optimized for downstream reporting and analysis.