NO C2C OR THIRD PARTIES- CANNOT WORK WITH SPONSORED CANDIDATES OR FUTURE SPONSORED CANDIDATES Preferred Charlotte based OR REMOTE EST/CST candidates - but Charlotte will be prioritized!
The Lead AWS Data Engineer/Data Architect will drive the design, architecture, and implementation of enterprise data engineering solutions across the AWS ecosystem. This role combines hands-on technical leadership with architectural ownership, partnering closely with data architects, data scientists, product owners, and business stakeholders to build scalable, secure, and reliable data platforms.
The Lead AWS Data Engineer/Data Architect will also mentor engineers, set engineering standards, and help shape the organization's data modernization and AI-readiness roadmap.
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
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
8+ years of experience in Data Engineering, including 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
~ Strong experience designing and implementing enterprise-scale data lake and data warehouse solutions using Lake Formation, Amazon Redshift, and Amazon Athena
~ Advanced SQL and data modeling expertise, including dimensional modeling, data vault, and large-scale data warehousing
~ Deep experience designing, developing, and optimizing scalable, resilient data pipelines within AWS environments
~ Strong understanding of distributed data processing frameworks, particularly PySpark and EMR
~ Advanced Python development skills with extensive hands-on experience using PySpark
~ 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
~ Experience leading cloud migration, modernization, and enterprise data platform initiatives
~ Strong understanding of data governance, metadata management, data quality frameworks, and observability principles
~ Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps
~ Knowledge of LLMs, RAG, and vector databases to support AI-powered applications and intelligent search
AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud certification
Experience implementing enterprise data governance and metadata management platforms
Experience with real-time analytics, event-driven architectures, and streaming data platforms
Knowledge of modern data architecture patterns including Data Mesh, Lakehouse, and domain-oriented design
Experience leading large-scale cloud transformation or enterprise data modernization programs
Experience creating AI applications with AWS Bedrock
The Lead AWS Data Engineer/Data Architect will drive the design, architecture, and implementation of enterprise data engineering solutions across the AWS ecosystem. This role combines hands-on technical leadership with architectural ownership, partnering closely with data architects, data scientists, product owners, and business stakeholders to build scalable, secure, and reliable data platforms.
The Lead AWS Data Engineer/Data Architect will also mentor engineers, set engineering standards, and help shape the organization's data modernization and AI-readiness roadmap.
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
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
8+ years of experience in Data Engineering, including 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
~ Strong experience designing and implementing enterprise-scale data lake and data warehouse solutions using Lake Formation, Amazon Redshift, and Amazon Athena
~ Advanced SQL and data modeling expertise, including dimensional modeling, data vault, and large-scale data warehousing
~ Deep experience designing, developing, and optimizing scalable, resilient data pipelines within AWS environments
~ Strong understanding of distributed data processing frameworks, particularly PySpark and EMR
~ Advanced Python development skills with extensive hands-on experience using PySpark
~ 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
~ Experience leading cloud migration, modernization, and enterprise data platform initiatives
~ Strong understanding of data governance, metadata management, data quality frameworks, and observability principles
~ Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps
~ Knowledge of LLMs, RAG, and vector databases to support AI-powered applications and intelligent search
AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud certification
Experience implementing enterprise data governance and metadata management platforms
Experience with real-time analytics, event-driven architectures, and streaming data platforms
Knowledge of modern data architecture patterns including Data Mesh, Lakehouse, and domain-oriented design
Experience leading large-scale cloud transformation or enterprise data modernization programs
Experience creating AI applications with AWS Bedrock
Data Architect (Charlotte) in charlotte at Unknown Company
This position is listed as full time and able to be worked remotely.