Manager, Data Engineering

Manager, Data Engineering 
Company Profile:
NPS Prism is a market-leading, cloud-based CX benchmarking and operational improvement platform 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.
Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world. While NPS Prism is its own company, 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 are 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 professionally and personally. 

About the Role 

We are seeking a Manager, Data Engineering, to lead a team of data engineers responsible for building and operating the data capabilities that support our product and analytics offerings. 

This role will require strong people leadership, structured execution, sound technical judgment, and experience working with modern data engineering platforms. 

The position will work closely with product, analytics, data science, engineering, and business stakeholders in a product-platform environment where data quality, reliability, 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. 

What You’ll Do 

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

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

• 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 data pipelines, data models, integrations, 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 and improve the reliability, quality, observability, lineage, monitoring, and operational resilience of production data pipelines and platform components. 

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

Required Qualifications 

• Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, or a related field. 

• 8 years of experience in data engineering, software engineering, data platforms, analytics, or a related technical role. 

• 2 years of direct people management experience, including managing engineers and developing high-performing engineering talent. 

• Experience leading engineering teams that build and operate data pipelines, data platforms, analytics products, or related data systems. 

• Solid understanding of data architecture, data modeling, ETL/ELT workflows, data integration, production data systems, and cloud-based data platforms such as Databricks or similar platforms. 

• Track record of leading Agile/Scrum delivery within a single 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. 

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

• Comfortable working in a flexible working model requiring occasional office visits. 

Preferred Qualifications 

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

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

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

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