Job Description
NO C2C OR THIRD PARTIES- CANNOT WORK WITH SPONSORED CANDIDATES OR FUTURE SPONSORED CANDIDATES
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Preferred Charlotte based OR REMOTE EST/CST candidates - but Charlotte will be prioritized!
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W-2 Only
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About the Role
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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.
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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.
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Key Responsibilities
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- 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
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Required Qualifications
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- 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
- 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
- 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
- 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
- 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
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Preferred Qualifications
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- 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
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