Top Tech Jobs & Startup Jobs in Charlotte, NC

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, SQL, and Delta Lake. Supports SQL Server, SSIS, and SSRS environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, applies data warehousing practices, and partners with business users, analysts, and IT teams to deliver reporting, analytics, and AI/ML solutions.

Designs, develops, and maintains Databricks ETL pipelines, data lake architectures, datasets, and data integrations supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains legacy systems, implements data quality controls, and supports data warehousing. Maintains SSRS reports and collaborates with business users, analysts, and IT teams to deliver reporting solutions. Documents work, communicates technical information, and contributes to AI-assisted development practices.

Modernize and evolve a large-scale React Native mobile app with offline-first architecture, BLE device integrations, local data storage and sync. Improve performance, reliability, and scalability, influence architecture, mentor developers, collaborate cross-functionally, and occasionally visit farms to understand user workflows.

Lead strategy and delivery for global People technology (Oracle HCM Cloud and connected systems). Translate People strategy into product roadmaps, govern configurations and data quality, manage integrations and releases, drive automation with AI, oversee change management, UAT, documentation, and stakeholder alignment to ensure scalable, compliant HR systems that support workforce planning and enterprise reporting.

Define and lead end-to-end cloud application and platform architecture, ensuring scalability, security, reliability, and cost efficiency. Partner with engineering, security, data, and product teams to design shared platform capabilities, data and integration patterns, governance, observability, and migration/modernization roadmaps. Provide technical leadership and mentor engineers and SREs.

Design, build, and deploy production-grade AI/ML solutions that convert complex, distributed farm data into actionable intelligence. Engineer features, select models, run experiments, and move models to scalable, real-time production. Integrate, fine-tune, monitor, and observe models on cloud infrastructure (AWS, Databricks). Partner with product, engineering and domain teams and contribute to user-facing experiences when needed.