Engineering Team Lead (Hybrid)

Vizient•Irving, TX

10d•$117,600 - $206,000•Hybrid

About The Position

The Engineering Team Lead will lead an engineering team responsible for designing, developing, and delivering scalable, high-quality software solutions, including the Spend Manager Intelligence Platform for actionable insights and data-driven decision-making. The position combines hands-on technical leadership with team leadership, maintaining strong engineering practices while fostering a collaborative, high-performing environment. The lead partners with Product, Architecture, and Delivery teams to align technical execution with business goals, coaches and mentors team members, and promotes continuous improvement. The role also champions emerging technologies, including AI-driven tools, and guides development of scalable data platforms, pipelines, and analytics capabilities using technologies such as Databricks and Spark. This position requires working from the Irving, Texas office three days per week and includes an in-person interview. The estimated salary range is $117,600 to $206,000, with incentive eligibility. Compensation varies based on skills, experience, organizational needs, and geographic factors.

Requirements

Seven or more years of software development experience.
Two or more years of experience leading or mentoring engineering teams.
Strong experience with modern software development practices, including CI/CD, testing, and application security.
Proficiency in one or more programming languages such as Java, Python, C#, or JavaScript.
Experience working with cloud platforms such as AWS, Azure, or GCP.
Experience designing scalable systems, including microservices and distributed architectures.
Strong problem-solving, analytical, and troubleshooting skills.
Experience working in Agile environments and collaborating with cross-functional teams.
Ability to communicate technical concepts to technical and non-technical stakeholders.
Experience with data engineering technologies such as Apache Spark, Databricks, and distributed data processing frameworks.
Hands-on experience building and maintaining data pipelines and large-scale data platforms.
Experience with streaming technologies and real-time data processing.

Nice To Haves

Bachelor’s degree or equivalent experience.
Demonstrated ability to mentor and develop engineers, fostering technical and professional growth.
Passion for innovation, continuous improvement, and emerging technologies.
Familiarity with data modeling, data warehousing, and lakehouse architectures.
Exposure to AI/ML workflows or data-driven applications.

Responsibilities

Lead the design, architecture, and development of scalable, high-performance software solutions.
Guide the team through complex technical challenges and ensure sound engineering decisions.
Contribute to the codebase by delivering efficient, maintainable, and secure code.
Ensure adherence to engineering best practices, including code reviews, testing, CI/CD, and application security.
Partner with Product Owners and stakeholders to understand requirements and ensure successful delivery.
Break down complex initiatives into actionable work and prioritize effectively.
Identify and communicate risks and provide mitigation strategies to support delivery timelines.
Foster a healthy, collaborative team environment that supports engagement and productivity.
Provide ongoing coaching, mentorship, and feedback to support individual and team development.
Address team dynamics and resolve conflicts with empathy and professionalism.
Promote accountability, continuous improvement, and a strong feedback culture.
Lead team retrospectives and drive process enhancements.
Advocate for and support adoption of AI and automation tools to improve engineering efficiency.
Identify opportunities to enhance workflows through emerging technologies.
Encourage experimentation and innovation within the team.
Communicate project status, progress, and risks to Product Owners, Delivery Leads, and stakeholders.
Collaborate cross-functionally with Architecture, Engineering, CloudOps, and Security teams to ensure alignment.
Guide development of scalable data platforms, pipelines, and analytics capabilities using technologies such as Databricks and Spark.