Data Engineer - Sr. Consultant

Visa•Bellevue, WA

3h•Hybrid

About The Position

Visa is building a next-generation Agentic AI and Data Platform to enable intelligent automation, adaptive workflows, and data-driven decision-making across our global post-purchase ecosystem. As a Data Engineer, you will lead the architecture, modernization, and scaling of Visa’s enterprise data infrastructure—bridging the existing SQL Server–based data warehouse with the new Hadoop and Databricks data lake platform. You will ensure seamless data flow, optimized performance, and integration of data services that support AI, GenAI, and Agentic systems. This is a hands-on leadership role requiring deep data engineering expertise and the ability to work across both legacy modernization and new platform innovation. You will collaborate closely with the Principal Agentic Engineer, ML teams, and business stakeholders to enable AI-driven insights and intelligent data orchestration. This is a hybrid position. The expectation for in-office days will be confirmed by your hiring manager. This role does not offer relocation or immigration support now or in the future.

Requirements

8 or more years of relevant work experience with a Bachelor’s 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, OR 11+ years of relevant work experience.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
Proven success supporting and modernizing SQL Server–based data warehouses in high-SLA environments.
Production-level experience architecting Hadoop, Spark, and Databricks data pipelines.
Expertise in ETL/ELT frameworks, data modeling, and schema design for analytical and operational use cases.
Strong programming proficiency in Python, Java, or Scala.
Strong SQL optimization, debugging, and production troubleshooting experience.

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
Hands-on experience with AWS or Azure (Glue, Synapse, Redshift, Delta Lake, S3).
Familiarity with Kafka, Airflow, Kubernetes, and containerized data services.
Understanding of RAG pipelines, vector databases, and AI data flows.
Experience designing data pipelines and APIs compatible with Model Context Protocol (MCP)-based agent frameworks, enabling seamless integration between AI agents, data services, and enterprise APIs
Experience leading data warehouse migration or modernization from SQL Server to Hadoop/Spark ecosystems.
Deep understanding of data lineage, metadata management, and governance frameworks (e.g., Atlas, Great Expectations).
Familiarity with LangChain, LangGraph, and MCP for integrating AI agents with data systems.
Strong ability to balance innovation and stability across coexisting legacy and modern data architectures.
Proven track record mentoring engineers and collaborating across global teams.

Responsibilities

Data Platform Modernization: Lead the transition from SQL Server data warehouse to the next-generation Hadoop/Databricks platform, ensuring performance, reliability, and minimal business disruption. Architect hybrid data pipelines that bridge legacy and modern ecosystems, enabling near real-time data access for analytics and AI applications. Optimize existing SQL Server models (facts, dimensions, indexes, stored procedures) and design modern equivalents in Hadoop and Spark environments. Define long-term migration strategy, data partitioning, and retention policies aligned with Visa’s data governance standards.
Data Architecture & Engineering: Design and implement scalable, distributed data pipelines using Spark, Kafka, Airflow, and Delta Lake. Build robust ETL/ELT frameworks to process transactional, behavioral, and unstructured data at scale. Partner with the Agentic AI team to power RAG (Retrieval-Augmented Generation) pipelines, vector database integrations and LLM data provisioning. Lead proof-of-concept (POC) initiatives to evaluate and integrate new data engineering technologies.
Operational Excellence: Provide guidance to junior Engineers to maintain existing SQL Server–based data warehouses, including database performance tuning, replication, encryption, and high-availability (HA) solutions. Implement best practices in T-SQL development, schema design, and stored procedure optimization. Perform proactive performance analysis, troubleshooting, and resolution of production issues in SQL Server and Hadoop clusters. Collaborate with DBA and application teams to ensure uptime within SLAs and compliance with Visa’s data policies.
Security, Governance & Compliance: Define and enforce standards for data quality, lineage, and governance across both legacy and modern platforms. Ensure full compliance with Visa’s data privacy, encryption, and access control frameworks. Partner with InfoSec to embed data security principles into every phase of data lifecycle management.
Leadership & Collaboration: Mentor and coach data engineers, fostering an environment of technical excellence and innovation. Collaborate cross-functionally with product, ML, and platform engineering teams on architecture decisions and roadmap execution. Serve as a bridge between legacy enterprise data teams and next-gen AI platform engineers, ensuring knowledge continuity and execution speed.