Top Senior Data Engineer Jobs in Raleigh, NC

Design, build, and maintain BI-ready datasets, dashboards, and monitoring tools for high-throughput lab operations. Implement process monitoring (SPC), ensure data quality and audit readiness, perform root-cause analysis, and partner with Data Science to deploy predictive models that improve throughput, quality, and compliance.

Design and build data infrastructure and pipelines, implement data architecture strategies, analyze complex issues, mentor junior team members, ensure data governance and security compliance, and develop client relationships to deliver actionable insights.

Senior Data Engineer in PwC's Managed Data, Analytics & Insights team responsible for designing and implementing scalable data solutions, building and managing advanced data ecosystems, solving complex problems, mentoring junior staff, and maintaining high delivery standards while building client relationships and understanding business context.

Design, build, and maintain data infrastructure, pipelines, and ETL/ELT workflows using cloud and big-data platforms. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, modeling, and orchestration tools to deliver scalable analytics solutions.

Lead design and delivery of cloud-based data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Manage and mentor a team, ensure data governance and security, implement IaC and DevOps, troubleshoot pipelines, collaborate with stakeholders, and drive data-driven decision making across client engagements.

Lead data architecture and engineering efforts: design and implement data infrastructure and pipelines, develop data models and flow diagrams, ensure governance and security compliance, manage large-scale projects, advise clients strategically, and coach high-performing teams to deliver analytics solutions.

Lead analytics engineering initiatives, design data pipelines, develop business intelligence solutions, and ensure data governance while collaborating with stakeholders.

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.

As a Senior Data Engineer, you will implement data ingestion patterns, build pipelines in Azure, and enhance development with AI tools, aiding the migration to a cloud-based architecture.

Lead data engineering efforts within Technology Consulting: design and maintain data architectures and pipelines, apply advanced analytics, implement BI solutions, coach teams, manage client relationships, and drive solution optimization, performance tuning, and service-level outcomes for managed services engagements.

Lead and deliver data engineering engagements: design and build ETL/ELT pipelines, implement cloud analytics solutions, mentor teams, manage client relationships, and ensure project delivery and standards adherence.

Design, build, and maintain scalable data pipelines and BigQuery-based data lake solutions on GCP. Optimize pipelines for performance and cost, enforce data quality, develop schemas and models, automate with Python and Terraform, integrate CI/CD, monitor and troubleshoot infrastructure, and collaborate with analysts and data scientists to deliver analytics-ready data. Document processes and apply healthcare PHI governance and security best practices.

Lead design, build, troubleshoot, and deliver enterprise-scale data solutions on Azure and Hadoop. Provide technical oversight, mentoring, enforce standards, code, unit test, and collaborate with cross-functional partners to implement scalable data pipelines and analytics platforms.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Design, develop, test, deploy, and maintain scalable ETL and BI/data warehouse solutions in cloud/on-prem environments. Build CI/CD pipelines, automation, test frameworks, and data quality processes. Collaborate with analysts and engineers in Agile teams to deliver reliable, observable, enterprise-grade data platforms.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.