Data Engineer Jobs in Durham, NC

Lead the design and development of data systems for cancer detection, collaborating with scientists and engineers to deliver robust datasets and improve data quality.

Lead database engineering for mission-critical platforms: administer Oracle and other databases, perform performance analysis and query tuning, design database solutions and replication, run POCs for new technologies, define standards for operations/migrations/onboarding, collaborate with enterprise teams, and produce technical documentation.

Lead design and build scalable data ingestion and feature pipelines for foundation models; implement data quality monitoring; model and integrate new data sources; run experiments measuring data impact; optimize ML training and hyperparameters; collaborate with ML, platform, and infra teams; lead technical initiatives and mentor team members.

The Data Engineer I will build and maintain data pipelines, contribute to platform code, and integrate data sources while growing alongside senior engineers in a production-focused role.

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.

Designs and delivers data lakes, data warehouses, and reporting platforms. Builds and maintains ETL/ingestion pipelines into Snowflake, supports multiple source databases, implements data masking and reconciliation, and automates CI/CD deployments using AWS, Python, Jenkins/Concourse and related tools. Performs testing, documentation, post-install validation, and project planning across multiple initiatives in a financial services environment.

Design, build, and operate end-to-end ELT data pipelines on Azure/Databricks using PySpark, Delta Lake and DLT; implement data quality, CDC, schema management, orchestration, monitoring, and publish analytics-ready datasets for Power BI while supporting governance, CI/CD, and operational runbooks.

Responsible for IT strategy and solutions in R&D, overseeing system integration, stakeholder collaboration, and project prioritization at Zoetis.

Design, build, and modernize full‑stack web applications and microservices for a real‑time event-driven data and visualization platform. Develop and optimize streaming data pipelines (Kafka, Flink, Spark), integrate observability, caching (Redis), and AI agents, and collaborate with hardware verification teams for scalable, low-latency solutions.

The Software Engineer will be responsible for data collection and management, enhancing the cloud infrastructure, and collaborating on AI datasets to support model training.

The Senior Data Engineer will design and implement data engineering solutions, maintain data pipelines, and ensure data security and governance practices while collaborating with teams to meet business requirements.

Define and lead the technical architecture for a lakehouse on AWS, build production pipelines and data models for time-series and multi-source data, introduce data governance and catalog foundations, author platform playbooks (ADRs, runbooks, Terraform modules), deliver projects end-to-end, and mentor engineers while representing the platform to senior leadership and non-technical stakeholders.

Designs and develops cloud-native ETL/ELT solutions and data warehouses using Informatica, Python, Oracle/PLSQL and scheduling tools. Architects data pipelines, optimizes SQL performance, automates jobs, supports testing and implementation, and documents applications across multiple projects.