At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.
In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
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.
About the Role
We are looking for a
Data Engineer
with strong expertise in
SQL Server, Data Warehousing, SSIS, and Data
Modeling
, combined with
hands-on experience in AI/LLMs
, especially for enabling
agentic AI capabilities within reports, portals, and data products
. This role involves designing scalable data pipelines, modernizing legacy systems, and integrating AI-driven components that enhance automation, insights, and user experience.
Responsibilities
Data Engineering & Development
Develop and optimize SQL queries, stored procedures, and ETL pipelines.
Build robust
data warehouse
structures and maintain /create high-quality ETL workflows using SSIS and Snaplogic .
Implement data quality, validation, and auditing frameworks.
AI & LLM-Driven Solutions (Agentic AI)
Apply
hands-on experience with AI/LLM tools and frameworks
to embed intelligence into reports, portals, and automations.
Build
agentic AI components
that can interpret user questions, summarize insights, trigger actions, and create contextual data responses.
Utilize LLMs to accelerate ETL documentation, metadata enhancement, pattern detection, and automated data transformations.
Collaborate with product and analytics teams to design
AI-enabled user journeys
, such as natural-language querying, conversational interfaces, and intelligent data assistants.
Data
Modeling
Design conceptual, logical, and physical models optimized for analytics, AI consumption, and enterprise data platforms.
Implement best practices in dimensional modeling (Star/Snowflake schema).
Align data structures with business needs and AI-driven workflows.
Required Skills & Experience
Strong hands-on expertise with SQL Server, SSIS, and Data Warehousing concepts.
Proven experience designing ETL/ELT solutions and optimizing large-scale datasets.
Knowledge of Python or scripting for AI & ETL automation.
Exposure to building conversational interfaces, natural-language query layers, or AI copilots.
Solid understanding of data modeling techniques and semantic layer design.
Practical, hands-on experience with LLMs and AI frameworks (OpenAI, Azure OpenAI, LangChain , etc.).
Ability to build or integrate agentic AI workflows into applications, reports, or data products.
Experience with cloud data tools and services (Azure, AWS, G CP etc. ).
Comfort with version control, CICD, and modern engineering practices.
Preferred Qualifications
Exposure to SSAS
Understanding of data security, compliance, and governance frameworks.
Exposure on cloud migration projects
Mandatory skill sets:
Data Engineer, Python
Preferred skill sets:
Data Engineer, Python
Years of experience required:
6-12 yr
Education qualification:
BE/B.Tech/MBA/MCA/Mtech/MSC/BSC
Education
(if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Technology, MBA (Master of Business Administration), Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications
(if blank, certifications not specified)
Required Skills
Data Engineering
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline {+ 38 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
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