Manager, Engineering (When submitting your application, please consent to complete the AI Interview — it helps us evaluate your profile more thoroughly and can speed up your next steps.)

Company Profile:

NPS Prism is a market-leading, cloud-based SaaS business owned by Bain & Company. NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences. Based on rock-solid sampling, research, and analytic methodology, it lets customers see how they compare to their competitors on overall NPS®, and on every step of the customer journey.

With NPS Prism you can see where you're strong, where you lag, and how customers feel about doing business with you and your competitors, in their own words. The result: Prioritize the customer interactions that matter most. NPS Prism customers use our customer experience benchmarks and insights to propel their growth and outpace the competition.

Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world. NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a company consistently recognized as one of the world's best places to work. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally.

Position Summary:

We are seeking a Manager, Engineering, to lead a team of engineers responsible for building the platforms and capabilities that support our product and analytics offerings. This role requires strong people leadership, structured execution, sound technical judgment, and experience working with modern data platforms with the versatility to guide engineers across multiple disciplines toward a shared set of outcomes.

The position will work closely with product, analytics, data science, engineering, and business stakeholders in a product-platform environment where reliability, quality, governance, and scalability are important to client and business outcomes.

The role is based in Gurugram, India, with a flexible working model requiring occasional office visits.

Key Responsibilities:

Manage, mentor, and develop a team of data engineers, data scientists, and software engineers, supporting feedback, coaching, performance management, hiring, onboarding, and retention.

Build a team culture grounded in ownership, accountability, collaboration, technical curiosity, and continuous improvement across disciplines.

Own sprint planning, backlog refinement, estimation, capacity planning, and Agile practices to improve focus, predictability, delivery quality, and continuous improvement.

Coordinate team execution across product priorities, platform improvements, technical debt, operational support, and stakeholder commitments.

Partner with product managers and stakeholders to translate business and product priorities into clear plans, milestones, and team-level commitments.

Provide technical oversight across the team's systems and platform components, partnering with technical leads, architects, infrastructure, security, and platform teams to balance reliability, scalability, governance, compliance, cost, and production readiness.

Promote engineering best practices across disciplines and improve the reliability, quality, observability, and operational resilience of production systems.

Communicate plans, risks, dependencies, trade-offs, and recommendations clearly to technical and non-technical stakeholders.

Required Qualifications, Experience & Skills:

Educational Qualifications

Bachelor's or master's degree in Computer Science, Engineering, Information Systems, or related field.

Experience:

8 years of experience in engineering or a related technical role, with strong depth in at least one of data engineering, data science, or software engineering, and the versatility to grow into managing across the others over time.

2 years of direct people management experience, including managing engineers across different technical disciplines and developing high-performing talent.

Experience leading engineering teams that build platforms, products, or systems, with an openness to broadening scope over time.

Skills:

Solid understanding of software architecture, data modeling and integration, and production systems, along with exposure to cloud-based platforms such as Databricks, Azure, or similar.

Track record of leading Agile/Scrum delivery within an engineering team, including sprint planning, backlog management, estimation, and continuous improvement.

Strong planning, execution, and stakeholder management skills, with experience partnering across engineering, product, and cross-functional business teams.

Strong communication skills, with the ability to work effectively with technical and non-technical stakeholders across multiple disciplines.

Good understanding of security, privacy, compliance, and governance practices, with a continuous learning mindset and passion for Agile principles and engineering excellence.

Preferred Qualifications

Familiarity with AI technologies, AI-enabled data platforms, and their application in data engineering workflows.

Experience using Agile, engineering, or delivery metrics to identify bottlenecks and improve team effectiveness.

Experience applying security, privacy, compliance, or governance practices.

Familiarity with Jira, Confluence, and the broader Atlassian toolset.

Prior experience managing a team with more than one distinct technical specialty (for example, a mix of data engineers, data scientists, and software engineers).