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Data & Backend Engineer (Full Stack) – Senior Associate

Hyderabad, Telangana
Engineering - Architecture
#778641
Remote / WFH
PwC Acceleration Center India

Job Description

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.

As a Data & Backend Engineer (Full Stack) – Senior Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Data and Analytics Engineering practice, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. As a Senior Associate, you will focus on building meaningful client connections and learning how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality work while embracing increased ambiguity.

In this role at PwC Acceleration Center India, you will work on exploratory and descriptive analysis, statistical modeling, and creating data visualizations to help solve complex business problems and inform strategic decisions. You will use a broad range of tools, methodologies, and techniques to generate new ideas and solve problems, interpreting data to inform insights and recommendations. Upholding professional and technical standards, you will develop a deeper understanding of the business context and how it is changing, using reflection to enhance strengths and address development areas.

Responsibilities
• Designing and developing robust data solutions using advanced technologies and techniques to transform raw data into actionable insights
• Leveraging statistical modeling and data visualization to solve complex business problems and inform strategic decisions
• Conducting exploratory and descriptive analysis to extract insights from large datasets and drive data-driven decision making
• Utilizing programming languages such as C++, R, and MATLAB to enhance data science workflows and troubleshoot algorithms
• Implementing machine learning and deep learning techniques, including neural networks and natural language processing, to optimize data analysis
• Building and maintaining data pipelines and data lakes to support efficient data mining and modeling
• Collaborating with AI-driven automation teams to integrate cognitive solutions into data engineering processes
• Validating data quality and integrity within analytics frameworks to support informed decision-making and business growth
• Guiding junior team members in the application of analytical thinking and complex data analysis techniques

What You Must Have
• At least a Bachelor's degree
• At least 4 years of experience
• Oral and written proficiency in English required

What Sets You Apart
• Proven experience in backend and data engineering
• Skilled in Python, PySpark, and SQL programming
• Hands-on experience with RESTful and GraphQL APIs
• Ability to develop front-end applications using ReactJS
• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating proficiency in data engineering and data science workflows
• Utilizing advanced programming languages such as C++, R, and MATLAB
• Applying machine learning techniques and predictive modeling in complex scenarios
• Leveraging experience with data lakes, data pipelines, and data quality management
• Excelling in analytical thinking and complex data analysis
• Navigating AI-driven automation and cognitive solutions effectively
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