Lead AI & Data Engineer

Brown‑Forman Corporation • Louisville, KY

4d • Hybrid

About The Position

Join our team and help shape the data foundation that will power Brown-Forman’s next generation of analytics and AI capabilities. As the Lead AI & Data Engineer, this role offers the opportunity to accelerate our digital transformation by building a trusted, scalable cloud data foundation essential for analytics, reporting, Master Data Management (MDM), and future AI capabilities. Bring strong engineering discipline, curiosity, and business partnership to solve meaningful problems, modernize how we work with data, and make a visible impact across the enterprise. Collaborating closely with business and technology teams, this position will translate high-value business problems into production-grade data solutions, while also helping to shape next-generation AI applications such as RAG, conversational AI, and agentic workflows.

Requirements

• 3+ years of dedicated experience in Data Science, Data Engineering, or AI, or 7+ years of combined work and education experience.
• Experience building and deploying production-ready data and AI solutions.
• Strong understanding of modern data architectures, cloud technologies, and analytical platforms, with the ability to select and apply the appropriate tools for a given business challenge.
• Strong Python and advanced SQL skills, with the ability to build scalable, maintainable, and well-tested data pipelines and optimize complex transformations and queries.
• Experience partnering with Enterprise Architecture, Integration, and Data Engineering teams to support the design and implementation of modern data lakehouse and cloud data platform architectures that enable advanced analytics, AI, and business solutions.
• Proven ability to work directly with business stakeholders, translate non-technical needs into technical requirements, and communicate technical decisions and tradeoffs clearly.
• Experience integrating disparate systems through APIs, batch interfaces, and SaaS platforms, with attention to reliability, security, monitoring, and error handling.
• Experience with data modeling, data quality controls, reconciliation, lineage, and operational support for enterprise data pipelines.
• Familiarity with Master Data Management concepts, including master-data domains, data stewardship, data quality rules, match/merge logic, survivorship, golden records, and governance.
• Experience enabling BI and reporting tools such as Tableau and/or AWS Quick.
• Exposure to model evaluation, prompt engineering, or model customization techniques.

Nice To Haves

• Experience with AWS cloud services is preferred, including designing and operating scalable data, analytics, and AI solutions.
• Experience with Databricks and modern data lakehouse architectures is preferred, including data engineering, analytics enablement, governance, and preparation of trusted datasets that support advanced analytics and AI applications.
• Experience building or supporting RAG applications, conversational AI solutions, AI agents, or LLM-powered business applications is preferred.
• Familiarity with Hadoop, Cloudera, and/or Impala environments is a plus.

Responsibilities

• Partner directly with business stakeholders to understand needs, clarify ambiguity, and translate business problems into clear technical requirements, data products, and delivery plans.
• Help drive the modernization of data infrastructure from on-premises platforms to cloud-based solutions. Design and implement scalable data lakehouse patterns that support reliable ingestion, transformation, storage, and consumption of enterprise data.
• Partner with Data Engineering teams to design, build, and operate resilient, reusable ETL/ELT pipelines using Python, SQL, APIs, and cloud-native services. Collaborate on integrating data from SaaS platforms, enterprise applications, and other source systems into the enterprise data ecosystem while adhering to established data architecture standards, governance, and controls.
• Develop analytical models, AI-enabled solutions, and decision-support capabilities that drive business value. Work closely with Data Engineering, MDM, and business stakeholders to identify, validate, and prepare trusted data needed for reporting, advanced analytics, machine learning, and intelligent automation initiatives.
• Prepare governed, discoverable, and high-quality data that powers LLM, RAG, vector-search, conversational AI, and agentic applications. As the enterprise data foundation evolves, contribute to the design, development, and deployment of AI-enabled business solutions. Partner with business stakeholders and the AI Center of Excellence to deliver secure, scalable solutions that adhere to governance, security, compliance, and responsible AI standards.
• Enable trustworthy, performant datasets for Tableau, AWS Quick, and other reporting experiences. Support the modernization and rationalization of reporting layers as the cloud data platform evolves.
• Develop, test, deploy, monitor, and document production-grade data solutions. Establish high standards for code quality, observability, reliability, security, and maintainability.
• Bring a pragmatic, hands-on approach to solving complex problems. Share engineering practices, coach peers, and help raise the team’s capability in cloud data engineering and AI-enabled delivery.

Benefits

• equitable pay structures for individual and company performance
• premium employee experience
• premium benefits that reflect our company values and meet the needs of our diverse workforce

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed