Lead Data Engineer

Hybrid to Charlotte is preferred Lead Data Engineer Core Technical Skills • 8+ years of experience in Data Engineering with at least 5+ years working extensively within AWS ecosystems • Expert-level experience with AWS services including S3, EMR, Glue Jobs, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions • Experience creating AI applications with AWS Bedrock • Strong experience designing and implementing enterprise-scale data lake and data warehouse solutions using Lake Formation, Amazon Redshift, and Amazon Athena • Extensive experience with Kafka-based streaming architectures, preferably Confluent Kafka • Advanced SQL and data modeling expertise, including dimensional modeling, data vault, and large-scale data warehousing solutions • Deep experience designing, developing, and optimizing scalable, resilient data pipelines within AWS environments • Strong understanding of distributed data processing frameworks, particularly PySpark and EMR • Expert knowledge of database management principles, performance tuning, and data architecture best practices • Advanced Python development skills with extensive hands-on experience using PySpark • Expertise in Infrastructure as Code using Terraform • Experience designing and implementing CI/CD frameworks using GitHub and GitHub Actions • Deep knowledge of AWS IAM roles, policies, governance, and security best practices • Strong experience with workflow orchestration tools such as AWS Step Functions, Apache Airflow, or equivalent platforms • Experience leading cloud migration, modernization, and enterprise data platform initiatives • Strong understanding of data governance, metadata management, data quality frameworks, and observability principles Core 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 Core Experience and Abilities • 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 multip…