Top Data Engineer Jobs in Greensboro, NC

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

As a Senior Data Engineer, you will manage data pipelines, ensure data quality, partner with teams for data-driven decisions, and improve the data platform while maintaining data integrity.

The Senior Data Engineer will create and manage data pipelines, ensuring data quality, collaborating with teams for data-driven decisions, and evolving the data platform.

Lead design and evolution of Foodsmart's data platform and pipelines, set architecture and standards for data quality, governance, and observability, enable analytics and ML at scale, mentor engineers, and drive platform-wide performance and reliability improvements.

Lead delivery of enterprise data governance, MDM, and modern data-platform components including Snowflake, CDC pipelines, schema-first contracts (JSON Schema/Avro/Protobuf), data catalog and PII classification, CI/CD schema management, AWS data services, and day-to-day leadership of an offshore delivery team.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.

Lead technical design and hands-on development of Pantheon’s data platform, extending ingestion, curation, retention services and ML/LLM infrastructure. Mentor engineers, drive architecture and engineering standards, operate in a DevOps model, partner cross-functionally, and participate in on-call support to ensure reliable, compliant data access and analytics.

Own and evolve the data platform: architect, build, and maintain data models, pipelines, and access layers. Ensure data quality, governance, and reliability; monitor and optimize infrastructure; provide technical leadership, code reviews, and collaborate with cross-functional teams to deliver scalable data solutions for operations and analytics.

Build and maintain scalable data pipelines and Python automations for ingesting, processing, and enriching data. Integrate SaaS sources via APIs, use Databricks/PySpark/Delta Lake and AI tools to power lead generation, enrichment, deduplication, and entity resolution. Collaborate cross-functionally to translate business needs into automated, production-ready solutions.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Lead a team to design, build, and maintain cloud data engineering solutions using Microsoft Fabric and Azure Synapse. Responsibilities include architecture, data pipelines, lakehouse and warehousing implementation, governance, performance optimization, mentoring engineers, cross-functional collaboration, support/on-call, documentation, and ensuring reliability and compliance.

Lead the vision and execution for scalable data governance and quality across Airbnb. Architect future-proof data ecosystems, define best practices and tooling, drive cross-functional policy implementation (privacy, legal, infosec), mentor senior engineers, and influence executive strategy to embed stewardship into the data product lifecycle.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.