Top Data Engineer Jobs in Charlotte, NC

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

Design, build, and maintain data pipelines and architectures, apply advanced analytics to generate client insights, develop BI dashboards, collaborate with stakeholders to solve data challenges, and support managed-services engagements while upholding technical and professional standards.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

As a Data Engineer II, you will build, scale, and optimize data platforms, focusing on ETL/ELT pipelines, and collaborate with data scientists and AI engineers to support data-driven applications and insights.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

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.

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.

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

The Principal GenAI Data Engineer will drive the design and implementation of scalable GenAI data platforms, focusing on robust data pipelines for structured and unstructured data. This role requires expertise in Python and AI data architecture, enhancing enterprise data capabilities.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

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, build, and support low-latency, high-availability market data infrastructure (including LSEG TREP). Develop automation and monitoring, troubleshoot real-time data delivery and symbology issues, improve resiliency and failover, execute upgrades, and collaborate with networks, vendors, and stakeholders to modernize and maintain enterprise market data platforms.

Lead Systems Operations Engineer responsible for production application support, ITIL-based incident/problem/change/release management, Workday and HR data distribution SME duties, and driving service maturity. Collaborates with development and business teams, runs incident bridges, leads root-cause analysis and remediation, implements automation/SRE practices, and configures observability tools like Splunk or AppDynamics. Provides documentation, runbooks, and training while participating in on-call rotation and vendor troubleshooting.

Lead delivery of enterprise data-at-rest encryption, tokenization, and key management solutions using Thales CipherTrust. Drive product roadmaps, risk management, stakeholder alignment, scalable onboarding patterns, automation with Ansible, and operations across Linux/Windows/AIX environments. Oversee policy, compliance, resource allocation, and continuous improvement for large-scale encryption deployments in regulated environments.

Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

The Lead Data Engineer delivers end-to-end data solutions, mentoring engineers, designing data architecture, and enhancing data pipelines across the organization.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Design, implement, and support Level 3/Level 4 data management, historians, and reporting solutions using industrial platforms. Integrate plant systems (DeltaV, OPC, Modbus, SQL), lead projects, author proposals, support deployments, and advise on data integrity, analytics, and visualization best practices.