required SW Development Manager, Data Exchange
The Intuit Data Exchange (IDX) is the data exchange hub for all Intuit businesses. Our teams empower our customers by acquiring the data they need, from numerous sources, while processing millions of transactions, statements, and other financial data points, a day. We are looking for an engineering manager to join our growing team.
Responsibilities
Lead a team of 6+ software engineers. Guide, coach and mentor them.
Be the teams technical authority, project and people leader
Contribute to the design and development of high-end, architecturally complex system
Build high performing teams by putting the right people in the right job at the right time
Evaluate employee performance, set expectations and goal for the department and individual staff members, recruit and train staff
Initiate and embrace innovative ideas that produce outstanding results for our customers
Establish and stimulate software development standards and processes along with best practices for the delivery of scalable and high-quality software
Create a shared vision and maintain strong cross-functional alignment with partners across the business (for example Program Mgmt, Business Analyst, Products, and more)
Requirements: 2+ years of experience as an established technical leader of software engineering teams that have successfully delivered customer-driven software products
5+ years hands-on experience with Java, Spring Boot, AWS or similar
Demonstrated experience leading positive change, empowering people, cultivating product technology visions and innovative solutions, and fostering effective engineering teams
Experience working in a global organization and ability to think and act strategically for all stakeholders
A passion and high energy for problem-solving, flexibility, comfort with ambiguity, and creativity as part of a team.
Possesses strong verbal and written communication skills, both in Hebrew and English
BSc / MSc in Computer Science, or equivalent work-related experience
Advantage: experience working with data scientists and integrating production-grade ML models
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