Manager Data Engineering - Agentic AI

LexisNexis is a global provider of information-based analytics and decision tools for professional and business customers. The role of Manager Data Engineering involves providing leadership and direction to data engineering teams, ensuring high-quality data pipelines, and collaborating with various stakeholders to meet business goals.

Responsibilities:

• Team Leadership: Successfully partner and lead teams of resources (including offshore) in solving complex business needs. Carry out management responsibilities including interviewing, hiring, training, appraising performance, and rewarding/disciplining employees
• Technical Execution: Write advanced complex code for computer systems and serve as a senior source of expertise. Lead the development of technical standards and perform reviews to ensure enterprise and architectural standards and processes are followed
• Product & Business Support: Interact with Product Management, Engineering, and Operations teams to plan delivery of products and enhancements and to assure products meet requirements and quality standards. Provide design input across a product
• Communication: Serve as the primary technical point of contact for external technology resources. Communicate and present data issues and analysis to a wide audience, including senior management and customers
• Continuous Improvement: Manage continuous improvement initiatives and implementation of best practices. Identify opportunities for automation or other utilities. Exhibits innovative approaches to process improvement
• Project Management: Conduct project reviews, ensuring review criteria are defined, and implement procedures for ensuring quality control of project deliverables. Maintain flexibility to react quickly to changes in priorities or circumstances to meet the needs of the business

Requirements:

• 10+ years of experience in Data and Scoring Engineering, data management, and data strategy, with a strong technical background and demonstrated expertise in quality control processes and practices
• 2+ years' management experience
• Bachelor's Degree (Engineering/Computer Science preferred but not required); or equivalent experience required. Advanced degree preferred
• Advanced understanding of data engineering methodologies, processes, and process improvement
• Leads the development and execution of performance and automation scripts for large-scale projects, with a proven ability to develop and execute complex automated and performance scripts
• Knowledge in normalized/dimensional data modeling principles and their application to complex business needs. Expert knowledge of multiple data storage subsystems and large complex systems
• Strong proficiency in database technology, design and manipulation, optimization, and best practices. Strong proficiency with data manipulation language including optimization techniques. Strong proficiency in writing complex SQL queries (preferably MySQL) to retrieve data from multiple tables
• Strong research and problem-solving skills (tools/root cause analysis). Advanced problem-solving experience involving leading teams in identifying, researching, and coordinating resources to troubleshoot/diagnose complex project issues
• Ability to lead small to medium-sized team(s) and balance deployment of resources within the group as necessary to support priorities. Proven expert in partnering and leading internal and external technology resources in solving complex business needs
• Experience working with any large language model (LLM), preferably through API integration, to build, deploy, or enhance data-driven solutions. Demonstrated ability to leverage LLMs for developing automation scripts, optimizing workflows, or solving complex business needs
• Demonstrated expertise in crafting clear, targeted prompts to elicit precise responses from AI models and optimize automation or data-driven workflows
• Experience in using Jupyter or Databricks
• Experience related to Security Exchange Commission