Lead Software Engineer (Backend)

At Varicent, we’re not just transforming the Sales Performance Management (SPM) market—we’re redefining how organizations achieve revenue success. Our cutting-edge SaaS solutions empower revenue leaders globally to design smarter go-to-market strategies, maximize seller performance, and unlock untapped potential. Varicent stands at the forefront of innovation, celebrated as a market leader in the 2025 Forrester Wave Report for SPM , 2023 Ventana Research Revenue Performance Management (RPM) Value Index , Gartner Peer Insights , 2024 Gartner SPM Market Guide , and G2. Our solutions are trusted by a diverse range of global industry leaders like T-Mobile, ServiceNow, Wawanesa Bank, Shaw Industries, Moody's, Stryker and hundreds more. Here’s why you’ll thrive at Varicent:

• Innovate with Purpose: Build impactful solutions for customers worldwide.
• Join Excellence: Work in a diverse, collaborative, and innovative team.
• Shape the Future: Lead in redefining revenue optimization.
• Grow Together: Unlock your potential in a supportive environment.

Join us at Varicent—where your talent and ambition meet limitless opportunities for success!

Job Description

We’re building scalable, data-driven product systems and looking for a Lead Software Developer with strong engineering skills and a track record of designing and delivering complex, production-grade systems. You’ll lead the design and delivery of critical product components, collaborate closely with technical leads and senior stakeholders, and play a key role in driving technical quality, scalability, and engineering standards across a core product area.

Overview

• Own critical components end-to-end and deliver measurable improvements in system quality, scalability, and reliability. You operate independently, drive design decisions, and elevate engineering standards through technical leadership and mentorship.

What you’ll do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, C#, and AWS-native services.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.

Engineering Expectations

• Strong system design skills with the ability to break down ambiguous problems into scalable technical solutions.
• Ability to evaluate new technologies, tools, and approaches, and recommend solutions based on trade-offs, impact, and ROI.
• Builds systems that are secure, reliable, and compliant by design, partnering with cross-functional teams when needed.
• Drives technical alignment across teams and contributes to improving engineering standards and processes.

How we work

• We balance exploration with delivery — test ideas quickly, then productionize what works.
• “Done” means quality goals are met, followed by continuous improvement in scalability, performance, and reliability.
• The team owns systems end-to-end (build, release, reliability).

Required skills & knowledge

• 6+ years of backend or full-stack engineering experience with a strong backend focus.
• 3+ years working with Typescript / Node.js / C#.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Proven experience working with large datasets , distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Desired (nice to have)

• Experience building data-driven or ML-enabled systems
• Familiarity with experimentation frameworks, A/B testing, or performance optimization
• Experience with event-driven architectures, streaming systems, or large-scale data processing
• Exposure to modern AI tools or integrati