Data Engineer

Title: Data Engineer Hiring Location: Gurugram, India (Work From Home Role) Experience: 3–6 Years Employment Type: Full-time

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.

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.

We are seeking a highly skilled and experienced Data Engineer to join our team. The ideal candidate will have strong expertise in Python, SQL and PySpark, with proven experience working on Databricks and cloud platforms such as Azure and AWS. A solid understanding of ETL tools like Python as well as basic knowledge of DevOps practices and CI/CD pipelines, will be advantageous. This is a unique opportunity to work in a dynamic and fast-paced environment to design and implement robust data solutions for scalable business needs. Working with Git and versioning. Key Responsibilities:

Design, build, and optimize ETL/ELT workflows using tools like Databricks, SQL, Python/pyspark & Alteryx (Good to have).

Develop and maintain robust, scalable, and efficient data pipelines for processing large datasets. from source to emerging data.

Cloud Data Engineering:

Work on cloud platforms (Azure, AWS) to build and manage data lakes, data warehouses, and scalable data architectures.

Utilize cloud services like Azure Data Factory, AWS Glue, or for data processing and orchestration.

Use Databricks for big data processing, analytics, and real-time data processing.

​​​​​​​Leverage Apache Spark for distributed computing and handling complex data transformations.

Create and manage SQL-based data solutions, ensuring high availability, scalability, and performance.

​​​​​​​Develop and enforce data quality checks and validation mechanisms.

Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver impactful data solutions.

​​​​​​​Understand business requirements and translate them into technical solutions.

​​​​​​​ DevOps and CI/CD:

Leverage CI/CD pipelines to streamline development, testing, and deployment of data engineering workflows.

Work with DevOps tools like Git, Jenkins, or Azure DevOps for version control and automation.

Maintain clear documentation for data workflows, pipelines, and processes.

Optimize data systems for performance, scalability, and cost-efficiency

Required Qualifications, Experience and Skills

3–6 years of experience in Data Engineering or related roles.

Hands-on experience with big data processing frameworks, data lakes, and cloud-native services.