Staff Data Engineer (Individual Contributor) (India)

Job Description: Staff Data Engineer (Individual Contributor) – NPS Prism

Hiring Location: Gurugram India (Till 6 months Probation is complete Work From Office Then Work From Home Flexibility)
Experience: 8+ Years
Employment Type: Full-time

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 highly skilled and experienced Staff Data Engineer to join our team.

As a senior technical leader, you will be responsible for designing, building, and optimizing large-scale, high-performance data pipelines and architectures that power NPS Prism’s analytics and client-facing applications. This role requires deep Databricks expertise, proficiency in Python, SQL, and PySpark, and the ability to work across cloud-native environments (Azure, AWS, or GCP).

You’ll collaborate closely with data scientists, product managers, and business stakeholders to shape and execute the platform’s data strategy, ensuring data quality, scalability, and reliability at enterprise scale.

Key Responsibilities

Data Architecture & Engineering Leadership

• Design and own scalable data architectures for ingestion, transformation, and analytics on Databricks.

• Build robust ETL/ELT pipelines using PySpark, SQL, and Databricks Workflows.

• Lead performance tuning, partitioning, and data optimization across large distributed systems.

• Mentor junior data engineers and enforce best practices for code quality, testing, and version control.

Cloud & Platform Engineering

• Develop and maintain data lakes and data warehouses on cloud platforms (Azure Data Lake, AWS S3, GCP BigQuery, etc.).

• Utilize Azure Data Factory, AWS Glue, or similar orchestration tools to manage large-scale data workflows.

• Integrate multiple data sources (structured, semi-structured, and unstructured) into unified models for NPS Prism analytics.

Databricks & Advanced Analytics Enablement

• Leverage Databricks for large-scale data processing, Delta Lake management, and ML/AI enablement.

• Drive the adoption of Databricks Unity Catalog, governance, and performance features.

• Partner with analytics teams to enable seamless model training and inference pipelines on Databricks.

Data Quality, Observability & Governance

• Define and implement frameworks for data validation, monitoring, and error handling.

• Collaborate with platform teams to establish data lineage and governance using tools like Great Expectations, Monte Carlo, or Databricks-native observability.

• Ensure compliance with Bain’s data security and privacy standards.

DevOps & CI/CD for Data

• Implement CI/CD pipelines for data code deployments using Git, Azure DevOps, or Jenkins.

• Automate testing, deployment, and monitoring for data workflows to ensure reliability and repeatability.

Cross-Functional Collaboration

• Work with product and business teams to translate analytical requirements into scalable technical designs.

• Collaborate with Data Science and BI teams to deliver analytics-ready datasets for dashboards and models.

• Serve as a technical advisor in architectural reviews and strategic data initiatives within NPS Prism.

Required Qualifications, Experience & Skills:

Educational Qualifications

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

Core Technical Expertise:

• Advanced proficiency in Databricks (mandatory).

• Strong command of Python, SQL, and PySpark for big data processing.

• Experience with Delta Lake, Spark optimization, and cluster management.

• Hands-on with ETL/ELT design, data lake and warehouse architecture.

• Cloud expertise in Azure, AWS, or GCP (Azure preferred).

Leadership & Architecture:

• 8+ years of data engineering experience, with at least 3 years in a lead or staff-level role.

• Proven ability to design end-to-end data solutions and influence engineering best practices.

• Strong mentorship and stakeholder management skills.

Preferred Qualifications:

• Familiarity with streaming frameworks (Kafka, Event Hubs).

• Understanding of data modeling and BI integration (Power BI, Tableau).

• Exposure to DevOps, CI/CD pipelines, and Infrastructure as Code (IaC).

• Strong problem-solving and analytical skills.