Senior Azure Data Engineer

IN_Manager_AI Practioner_Data and Analytics_Advisory_Bengaluru

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

*Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "

Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Responsibilities:

Experience – 12+ Years Job Description · Lead design and deployment of advanced machine learning models, GenAI and Agentic AI solutions across domains · Drive the use of data science methodologies to solve complex business challenges · Architect modular, scalable AI systems using LLMs, autonomous agents, and orchestration frameworks · Knowledge of AI and ML frameworks with exposure to Neural Networks, Deep Learning and Transformer Architecture. · Experience in Developing AI ML solutions and Model optimisation and hyperparameter tuning. · Translate business problems into AI use cases and technical blueprints · Collaborate with engineering, product, and business teams to deliver AI-powered solutions · Drive client workshops, PoCs, and strategic roadmaps for AI transformation · Ensure ethical AI practices, governance, and compliance across deployments · Mentor teams transitioning from classical data science to GenAI paradigms · Contribute to thought leadership, IP development, and practice growth · Architect data-driven GenAI pipelines integrating data science models, predictive analytics, and LLM-based decision systems. · Collaborate with cross-functional teams to embed AI governance, bias detection, and data lifecycle management into GenAI and Agentic AI solutions. · Drive experimentation and innovation by applying reinforcement learning, data augmentation, and feedback-loop optimization to improve autonomous agent performance. Ways to Stand Out · Thought leadership in GenAI and autonomous systems · Ability to simplify complex AI constructs for business users · Experience driving AI transformation across industries · Able to understand classic AI and ML use case and scale it with Gen AI Technologies. · Strong problem-solving and analytical mindset · Comfortable working under tight timelines and managing multiple stakeholders

Mandatory skill sets:

· Deep expertise in Generative AI, Agentic AI, and LLM orchestration. · Hands-on experience with LangChain, LlamaIndex, OpenAI, Anthropic, or similar platforms · Strong foundation in Python, ML Ops, vector databases, and embedding models · Experience with cloud-native AI stacks (Azure AI, GCP Vertex AI, AWS Bedrock) · Proven ability to lead client-facing engagements and translate business needs into AI solutions · Familiarity with retrieval-augmented generation (RAG), autonomous agents, and tool use chaining · Prior experience in AI/ML, or classical ML/DL pipelines. · Exposure to AI cloud services such as Azure, AWS, or GCP. · Hands-on with orchestration-based AI frameworks and multi-agent systems.

· Strong knowledge of data science and machine learning principles, including supervised/unsupervised learning, feature engineering, and model evaluation. · Proven ability to integrate data engineering workflows (ETL, model pipelines, vector databases) with GenAI systems for contextual reasoning. · Experience building self-learning AI ecosystems using reinforcement learning or adaptive fine-tuning strategies.

Preferred skill sets:

· Prior experience as Data Scientist or classical ML expert · Certifications in GenAI platforms or cloud AI services · Exposure to AI product development, agentic workflows, or multi-agent systems · Strong communication and stakeholder management skills · Experience in proposal development, IP creation, and practice building · Exposure to data science frameworks like PyTorch, TensorFlow, or scikit-learn alongside vector databases such as Pinecone, FAISS, or Chroma. · Experience integrating classical ML models with LLM outputs for hybrid GenAI use cases (predictive + generative).

Years of experience required:

12+ years relevant experience with at least 3–5 years in GenAI/Agentic AI and client-facing role

Education qualification:

BE, B.Tech, ME, M,Tech, MCA (60% above)

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of EngineeringDegrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Artificial Intelligence (AI)

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

Experience Level

Mid Level