Assurance - RMS - Data and Analytics Engineering - QA Engineer – Associate

PwC Acceleration Center India; Kolkata District; On-site; INR 600,000 - 850,000; Full time

Job summary

PwC Acceleration Center India is seeking a QA Engineer – Associate to join our Data and Analytics Engineering team. You will transform raw data into actionable insights and build AI/ML solutions for clients, applying Python, Java, and open-source tools in a collaborative environment.

You'll learn through hands-on projects, contribute to data pipelines, and help deliver high-quality data products that drive decision-making across geographies.

Qualifications

• Bachelor’s degree required.
• English proficiency (oral and written) required.

Responsibilities

• Design AI systems to transform raw data into actionable insights.
• Develop and deploy machine learning models using Python and TensorFlow.
• Collaborate to integrate data pipelines and improve data quality.
• Utilize Java/Python for software development and AI implementation.

Skills

Python

Java

Data analysis

NLP

Open-source software

Education

Bachelor's degree

Tools

TensorFlow

Scikit-learn

Job description

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands‑on learning, cutting‑edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

Role Overview

As a QA Engineer – Associate within our Data and Analytics Engineering team, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision‑making and driving business growth. You will be part of a dynamic team that leverages advanced technologies and techniques to design and develop robust data solutions for clients. Within our Assurance practice, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning‑based solutions at scale. As an Associate, you will focus on learning and contributing to client engagement and projects while developing your skills and knowledge to deliver quality work.

Responsibilities

• Designing and implementing AI systems to transform raw data into actionable insights
• Developing and deploying machine learning models using Python and TensorFlow
• Collaborating with team members to integrate data pipelines and enhance data quality
• Utilizing C++ and Java programming languages for software development and AI implementation
• Conducting complex data analysis to identify patterns and inform decision‑making
• Building scalable data solutions that support business growth and client needs
• Engaging in data wrangling and modeling to enable effective AI model deployment
• Applying natural language processing techniques for text analytics and sentiment analysis
• Leveraging open‑source software to enhance AI and machine learning capabilities
• Participating in client support activities to deliver value and drive project success

What You Must Have

• At least a Bachelor’s degree
• Oral and written proficiency in English required

What Sets You Apart

• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Statistics, Mathematical Statistics, Data Processing/Analytics/Science, Artificial Intelligence and Robotics
• At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
• Demonstrating proficiency in Python and Java programming languages
• Utilizing machine learning libraries such as TensorFlow and Scikit‑Learn
• Engaging in complex data analysis and pattern recognition
• Applying AI implementation skills in client support environments
• Developing data integration and data quality solutions