Sr. Data Engineer

LexisNexis UK•Home based-North Carolina, NC

1d•$95,300 - $158,800

About The Position

The Sr. Data Engineer provides assistance and input to management, develops and leads large multifunctional development activities, solves complex technical problems, writes complex computer systems code, and serves as a senior source of expertise. The role may also provide sizing or budget recommendations to management. The position partners with cross-functional stakeholders to deliver analytics and technology solutions that support business goals. It leads development and maintenance of scalable data, analytics, and automation solutions, ensuring data quality, platform reliability, operational excellence, and efficient use of cloud and technology resources. The role also provides technical and people leadership, including developing teams, managing resources and delivery risks, and supporting strategic planning.

Requirements

Bachelor's or advanced degree in Computer Science, Engineering, Data Science, Statistics, or a related field, or equivalent practical experience.
Significant professional experience in one or more of data engineering; data science or machine learning; business intelligence or advanced analytics; or DevOps, DataOps, MLOps, or cloud-platform engineering.
Experience leading technical teams and managing people, capacity, and delivery while remaining hands-on technically.
Strong proficiency in SQL and at least one programming language, such as Python.
Experience designing and operating production-grade data, analytics, ML, or cloud-platform solutions.
Hands-on experience deploying AI solutions in production, including generative AI and LLM applications using patterns such as RAG, embeddings, vector databases, fine-tuning, and agentic workflows.
Experience with AI/ML frameworks and platforms such as PyTorch, Hugging Face, LangChain, Amazon Bedrock, Azure OpenAI, or Vertex AI.
Experience evaluating and monitoring AI systems for performance, quality, drift, latency, and cost, guided by responsible AI practices.
Ability to identify high-value AI use cases and deliver measurable business outcomes.
Working knowledge of cloud platforms, data warehouses or lakehouses, orchestration, CI/CD, and monitoring tools.
Strong understanding of data quality, governance, security, scalability, and reliability.
Proven ability to manage multiple initiatives and competing priorities in a changing environment.
Strong communication skills and ability to collaborate with technical teams, business stakeholders, and senior leadership.

Responsibilities

Partner with cross-functional stakeholders to deliver analytics and technology solutions that support business goals.
Prioritize the team roadmap, drive data-informed decision-making, and communicate progress and recommendations to leadership.
Ensure compliance with security, governance, and regulatory standards.
Define and measure success through business impact, solution quality, and user adoption.
Lead the development and maintenance of scalable data, analytics, and automation solutions.
Ensure data quality, platform reliability, operational excellence, and efficient use of cloud and technology resources while promoting modern engineering practices and automation.
Recruit, mentor, and develop technical teams across analytics and data disciplines.
Manage resources, budgets, priorities, and delivery risks while fostering accountability, collaboration, continuous improvement, and high-quality execution.
Provide technical leadership, support strategic planning, and serve as a subject-matter expert.
Remain hands-on technically while leading teams and managing people, capacity, and delivery.