Top Data Engineer Jobs in Charlotte, NC

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead and manage delivery of modern data ecosystems and managed data analytics programs. Oversee project planning, budgeting, quality, and client accounts. Mentor teams, drive data strategy, convert insights to business opportunities, and ensure standards and risk management across large transformations.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Develop and maintain data pipelines and ETL processes, optimize SQL and data architectures, build BI reports and dashboards (Oracle BI, QlikView, Spotfire), analyze data to produce strategic insights, support client engagements in regulated environments, and apply continuous process improvements to ensure data quality and integrity.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Configure and maintain Adobe Experience Platform and Real-Time CDP data pipelines, XDM schemas, datasets, identity resolution, Profile enablement, segmentation readiness, and destination activation. Validate data quality, troubleshoot ingestion and identity issues, manage sandboxes, and implement privacy, consent, governance, and access controls. Partner with architects, data engineers, consultants, analysts, data scientists, and marketing teams to support reporting, personalization, and machine learning readiness.

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.

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.

Design, build, and operate production AI and data systems for marketing: LLM/agent orchestration, retrieval pipelines, data pipelines, CDP and warehouse architecture, automation of manual workflows, data quality and reliability, stakeholder collaboration, and mentoring. Ship production-grade Python and SQL solutions and evaluate/monitor AI systems.

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 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.

Leads data center infrastructure service delivery, lifecycle management, engineering readiness, standardized provisioning, and implementation processes. Designs repeatable, automation-ready workflows using ServiceNow and supporting tools, translating business priorities into executable plans. Advises leadership on complex enterprise technology solutions across infrastructure, applications, networks, security, databases, operating systems, and web technologies. Drives innovation, risk management, operational efficiency, and resolution of large-scale technical challenges.

Design, build, and operate Lowe's scalable Search Platform using OpenSearch/Elasticsearch and GCP. Develop batch and near-real-time ingestion/ETL pipelines, cloud-native services, APIs, and CI/CD. Improve performance, reliability, monitoring, and mentor engineers while collaborating across teams.

Designs and operates scalable GCP data pipelines, reusable engineering frameworks, feature stores, orchestration workflows, and governed data models supporting AI and machine learning. Builds Python, SQL, and Beam transformation libraries; ensures workload cost, performance, reliability, quality, lineage, and observability; and partners with data scientists migrating models to GCP. The role also documents best practices, provides enablement, and supports production systems during off-hours.

Leads large-scale data engineering initiatives, including migrating SQL Server implementations to Databricks. Designs, codes, tests, documents, and reviews complex technology solutions while establishing engineering standards, guiding teams, resolving technical issues, and mentoring peers. The role supports advanced analytics, data governance, data onboarding, cloud technologies, and modern data architecture.

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.

Build modern data and AI analytics solutions using ThoughtSpot, Snowflake, semantic data layers, and governed data assets. Develop ETL processes, AI prompts, intelligent dashboards, and interactive analytics experiences for actuarial teams. Partner with business and analytics stakeholders to support pricing, reserving, underwriting, and portfolio decisions while surfacing trends, explaining business drivers, and enabling actionable recommendations.

Design, build, and operate scalable real-time and batch data pipelines ingesting high-frequency telemetry, simulation, and trackside data. Own Kafka/Flink streaming components, Databricks lakehouse implementations, and infrastructure-as-code deployments. Develop software in Python/Java/SQL, integrate systems, automate testing and releases, performance-tune pipelines, and mentor peers to ensure resilient, secure, high-performance data delivery for motorsports teams.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

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.

Build SDKs, self-service apps, and reusable abstractions for Coinbase's data platform. Develop data integration and processing tools, enable observability and security (cataloging, lineage, access controls), and collaborate with analysts, data scientists, and engineers to scale and operationalize data pipelines and models.

Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.

As a Senior Software Engineer on the Data Platform team, you'll enhance the data infrastructure, develop ETL pipelines, maintain data quality, collaborate across teams, and mentor junior engineers.