Lead Data Engineer

About the role

Primary Talent Partners has a new contract opening for a Lead Data Engineer with a large power and utilities client in Charlotte, NC. This is a 12-month contract with potential for extension.

Responsibilities

• Lead the design, architecture, and implementation of enterprise data engineering solutions across the AWS ecosystem
• Collaborate with Lead Developers, Data Scientists, Architects, Product Owners, and business stakeholders to define technical strategy and scalable solutions
• Provide technical leadership and mentorship to Data Engineers and development teams, promoting engineering excellence and best practices
• Drive key architectural decisions in partnership with Data Architects and Solution Architects to ensure scalability, security, reliability, and maintainability
• Design and oversee data warehouse and data lake solutions that balance business usability, performance, and long-term sustainability
• Establish engineering standards for data modeling, ETL frameworks, pipeline reliability, monitoring, and operational excellence
• Lead end-to-end solution delivery, ensuring alignment with business requirements, enterprise architecture standards, and regulatory requirements
• Oversee production support and operational management of AWS-based data platforms, driving root-cause analysis and performance optimization initiatives
• Champion data quality, governance, observability, and data stewardship practices across platforms and teams
• Identify opportunities to modernize data architecture and improve operational efficiency through automation and cloud-native technologies

Requirements

• Ability to lead hands-on development efforts while providing technical direction, code reviews, and engineering oversight across multiple initiatives
• Experience establishing development environments, infrastructure standards, security controls, and migration strategies across multiple AWS accounts and environments
• Ability to architect, develop, and govern enterprise-scale data pipelines, ETL processes, data ingestion frameworks, and orchestration workflows
• Proven ability to identify data gaps, define strategic remediation plans, and implement scalable automation solutions that improve analytical capabilities across the organization
• Ability to design and implement highly reliable data pipelines with strong focus on data quality, observability, resiliency, and operational supportability
• Experience building and optimizing large-scale data warehousing solutions that prioritize both business user experience and system performance
• Ability to drive technical decision-making, influence architectural direction, and effectively communicate complex technical concepts to both technical and non-technical stakeholders
• Proven track record mentoring engineers, fostering technical growth, and building high-performing data engineering teams
• Experience leading cross-functional initiatives involving data engineering, analytics, architecture, platform engineering, and business stakeholders
• Strong problem-solving and leadership skills with the ability to manage competing priorities in fast-paced enterprise environments
• Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps