Top Tech Jobs & Startup Jobs in Houston, TX

As a Senior Technical and Reporting Accountant, you'll work cross-functionally to address accounting issues, compile financial statements, assist with audits, and ensure compliance with US GAAP, particularly focusing on ASC standards. Training and collaboration on accounting topics will also be key responsibilities.

As a Customer Success Manager at Scratch, you'll develop expertise in financial products, build strong client relationships, drive growth through outreach and data analysis, and collaborate with internal teams to improve service delivery and client satisfaction.

The Software Engineering Manager will lead a high-performing engineering team, overseeing software application design, development, and deployment. This role requires mentoring engineers, fostering continuous improvement, ensuring adherence to best practices, and collaborating with cross-functional teams. The manager is expected to stay updated on industry trends to maintain competitive software solutions.

The Customer Success Manager will engage with Trauma Registry customers to ensure efficient product adoption and satisfaction following deployment, manage customer relationships, drive product renewal and expansion opportunities, and provide data-driven insights to enhance client workflows.

The Sr. Regulatory Product Subject Matter Expert at Tebra ensures compliance with health IT regulations, providing guidance on CMS & ONC regulations. This role involves leading product development efforts, educating teams on regulations, and driving the adoption of regulatory solutions, while collaborating with stakeholders and ensuring legal compliance.

The Senior Cloud Engineer will design and develop IT infrastructure architecture solutions, manage moderate to complex technical issues, drive automation, provide architecture recommendations, and maintain integrated technology systems. They will work closely with IT teams and be available on-call after hours.

The Data Engineer II role at Bestow involves building scalable data solutions, improving data quality and availability, creating data models and pipelines for analytics and machine learning, and collaborating with various teams to ensure efficient data management.