Top Data Engineer Jobs in Charlotte, NC

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.

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.

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

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.

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.

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.

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.

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.

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.

Lead design, build, and operate scalable, secure GCP data platforms and reusable data frameworks. Implement ingestion/transformation (batch/streaming), orchestration, data modeling, governance, observability, and CI/CD to enable self-service analytics and enterprise AI.

Design, build, and maintain optimized, highly available data pipelines and the BMG Data Warehouse. Lead medium-to-complex data integration, data modeling, code reviews, QA, and cloud migration efforts. Collaborate with business partners to translate requirements into solutions, resolve technical issues, and support analytics and reporting needs while adhering to policies and compliance.

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 of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

Data Engineer to develop data pipelines using AWS, Azure, or GCP, advise clients on cloud resources, and collaborate with stakeholders to enhance data architecture.

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.

The Senior Data Engineer will design, develop, and maintain robust data pipelines, collaborate with teams, and enhance data architecture.