Data Engineer ; Python, SQL, Databricks, Snowflake); Enterprise Platforms Technology

Data Engineer 5 (Python, SQL, Databricks, Snowflake) (Enterprise Platforms Technology)
** Position Overview
** We are seeking a Data Engineer to develop the technical vision, architectural design, and implementation of our AI-enabling data  this strategic role, you will bridge the gap between traditional enterprise data architecture and modern AI capabilities. You will design resilient, scalable data pipelines, and real-time streaming architectures that power LLM workflows, Retrieval-Augmented Generation (RAG) pipelines, and predictive ML models. You will work closely with Data Scientists, Analysts, and other Engineers to establish best-in-class data engineering practices for traditional and AI enabled workloads.

** About the Team
** The Enterprise Platforms Tech Top of House Data & Analytics team serves as the strategic intelligence backbone for executive leadership and strategy. We operate at the intersection of business strategy, core enterprise infrastructure, and advanced analytics. Our team is responsible for delivering high-impact, enterprise-level data products, decisioning engines, and modern analytics capabilities that power executive level decision-making.  
** Key Responsibilities
*** AI Architecture & Data Foundation:
Architect, build, and scale clean, reliable, and latency-optimized data pipelines (batch and real-time) designed specifically to supply structured, semi-structured, and unstructured data to AI/ML applications and Large Language Models (LLMs).
* Technical Leadership & Strategy:
Contribute to defining the architectural blueprint for the Top of House AI data layer. Serve as a hands-on technical lead, guiding junior and mid-level engineers in coding standards, design patterns, and engineering excellence.
* Data Governance, Security, & Lineage:
Partner with Enterprise Security and Data Governance teams to implement robust data classification, privacy safeguards, and automated lineage tracking for AI models and training datasets.
* Feature Engineering & Store:
Build and maintain scalable feature stores to support both real-time inferencing and offline model training across executive-facing predictive models.
* Performance & Cost Optimization:
Audit and optimize cross-cloud data pipelines, query performance, and storage infrastructure for efficiency, cost management, and reliability.

* Cross-Functional Collaboration:

Partner directly with Technical Program Managers, Data Scientists, Top of House leads, and C-suite stakeholders to turn executive data needs into production-ready solutions.  
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* Basic Qualifications:

*** Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
* At least 6 years of experience in application development (Internship experience does not apply)
* At least 4 years of experience in distributed data
* At least 4 years of experience with SQL
* At least 4 years of experience programming with at least one of the following languages:
Python, Java, or Scala
* At least 4 years of experience designing and developing data pipelines
* At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems  
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* Preferred Qualifications:

*** Master's Degree in a related field
* 9+ years of experience in application development including Python, SQL, Scala, or Java
* 5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
* 5+ year experience working on real-time data and streaming applications
* 5+ years of data warehousing experience (eg Snowflake)
* Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion…