Top Data Engineer Jobs in Charlotte, NC

Lead managed-data and analytics engagements to build modern data ecosystems, convert insights into strategy, manage client accounts, mentor teams, ensure project delivery, and uphold quality and governance standards.

Design and build data infrastructure, pipelines, and integrations across cloud platforms. Analyze complex problems, develop data architecture and models, mentor junior staff, ensure governance and security compliance, and build client relationships while enhancing technical skills and delivering high-quality project outcomes.

Design and implement scalable data solutions and manage advanced data ecosystems. Analyze complex problems, build ETL/ELT pipelines and data warehouses, maintain data governance, mentor junior staff, and cultivate client relationships to deliver high-quality managed data and analytics services.

Design, build, and maintain data infrastructure, pipelines, and integrations using cloud and big-data tools. Implement data lakes/warehouses, validate data quality, optimize performance, and collaborate with clients to deliver analytics and data strategy recommendations.

Lead design and delivery of data architecture, ETL/ELT pipelines, and data warehouse/lake solutions across cloud platforms. Coach and manage team members, ensure data governance/security compliance, partner with stakeholders, and improve data platform performance and cost efficiency.

Build and maintain data pipelines and ETL processes, optimize SQL and analytics, create BI reports/dashboards, design data architectures, support client engagements, and improve data quality in regulated environments while learning and contributing to projects.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, develop data models and pipelines, enforce governance and security, advise clients strategically, and coach/lead cross-functional teams to deliver data-driven outcomes.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Design and implement data architecture and scalable ETL/ELT pipelines using cloud platforms (AWS/Azure/GCP). Develop data models, ensure governance and security compliance, analyze complex problems, mentor junior staff, build client relationships, and enhance technical skills to deliver high-quality data solutions.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop and manage data lakes and warehouses, apply data architecture and dimensional modeling, validate data quality, implement security best practices, and collaborate with clients to deliver analytics and data strategies. Mentor peers and manage growing client responsibilities as a Senior Associate.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Lead design and modernization of scalable, secure data systems and real-time pipelines for xOT cybersecurity. Create data contracts, observability, lineage, and cross-functional solutions supporting cloud and on-prem deployments, Kubernetes, and stream processing to enable threat detection and intelligence.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As a Senior AI/Data Engineer, you will design and maintain scalable data and AI infrastructures, partnering with cross-functional teams to deliver reliable data systems and support AI-driven business capabilities.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Design, build and maintain scalable data pipelines and automated workflows using Python, Airflow, DBT and cloud warehouses. Partner with Analytics, Sales and Marketing to deliver curated marketing datasets, enforce data quality through validation and CI/CD, and support production deployment and monitoring of Enterprise Data Lake/ODS solutions.

Lead design, build, and operate reusable, secure, cloud-native data platforms on Google Cloud. Develop ingestion/transformation frameworks (batch/stream), orchestration (Composer/Workflows), shared libraries (Python/SQL/Beam), data modeling, governance-by-design, observability, cost/performance optimization, and enable self-service data consumption across teams.

Lead development and delivery of production-grade healthcare AI/GenAI solutions for health systems. Architect RAG and agentic AI pipelines, manage global data science teams and MLOps, process clinical and claims data, engage executive stakeholders, and ensure HIPAA-compliant deployments delivering measurable clinical and operational impact.

Lead design and delivery of data engineering solutions for clients: build and maintain data pipelines and architectures, implement BI and analytics (Redshift, DataStage, SQL Server, DB2), apply systems thinking, coach teams, manage managed-services/SLAs, validate outcomes with clients, and drive performance tuning and visualization using Python/Java and BI tools.

Lead and deliver data engineering projects, design and maintain ETL/ELT pipelines and architectures, implement cloud-based analytics (AWS/Redshift/S3/Glue), mentor teams, manage client accounts, promote BI/reporting and performance tuning, and drive process improvement to ensure project success and stakeholder value.

Lead design, implementation, and automation of Data Loss Prevention (DLP) and data protection controls. Onboard and integrate sensitive data sources, develop Python/Bash automation, troubleshoot complex security issues, perform risk assessments, evaluate new technologies, and mentor junior engineers while ensuring enterprise compliance and operational efficiency.

Lead engineering, design, and support of low-latency, high-availability market data platforms (LSEG TREP). Build and automate UNIX/Linux infrastructure, manage feed handlers, ensure resilient multicast/unicast distribution, resolve latency/feed issues, collaborate with networks/vendors, drive modernization, and maintain compliance and operational controls.