Top Tech Jobs & Startup Jobs in Charlotte, NC

The role involves supporting and improving software delivery pipelines, automating cloud infrastructure, and troubleshooting across pipelines, cloud, and configuration.

The Product Owner leads agile delivery teams, manages backlog, collaborates with product managers, ensures product strategies align with delivery, and oversees project execution and communication.

The Data Steward will perform data transformations and related activities in Databricks, maintain code, gather requirements, and ensure data quality.

Lead SRE role owning enterprise observability and monitoring strategy across cloud and applications. Architect Dynatrace-to-ServiceNow pipelines, alert correlation, paging integration, CMDB/service mapping, and automation for self-healing. Drive SRE practices (SLIs/SLOs/error budgets), mentor teams, reduce alert noise, improve MTTR, and standardize monitoring and incident workflows.

Design and implement scalable data architectures for analytics in the insurance industry, focusing on Databricks and data governance.

Oversee IAM program development, manage directory services, ensure compliance, lead implementation of IGA and PAM solutions, and mentor teams.

Manage day-to-day administration of equity compensation programs (stock options, RSUs), maintain equity data integrity and HRIS integrations, oversee transactions and vesting, ensure tax and regulatory compliance, coordinate with Finance/Legal/Payroll, prepare management and regulatory reports, manage vendor relationships, lead employee communications, and implement process improvements.

Lead software engineering services to align with strategic and operational goals, interface with executives, manage budgets, and ensure software quality and risk mitigation.

The Software Engineer will develop complex solutions, perform system integration, lead projects, and mentor junior developers while using various technologies and Agile practices.

As a Software Engineer in Machine Learning, you will develop and deploy production-grade ML solutions, collaborate with teams, and establish operational excellence in ML practices.