Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Senior Associate
& Summary
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.
Responsibilities
Fabric Platform Development: Design and implement Lakehouse, Data Warehouse, and Data Engineering solutions within Microsoft Fabric.
Data Pipeline Construction: Build, maintain, and optimize scalable end-to-end data pipelines using Fabric Data Factory (Dataflows Gen2/Pipelines).
Transformation & Processing: UtilizePySpark, Spark SQL, and SQL for data manipulation and transformation.
Data Architecture: Implement Medallion Architecture (Bronze/Silver/Gold) to ensure data quality and structure.
Data Virtualization & Storage: Use Fabric Shortcuts andOneLaketo manage data without moving it.
Real-time Analytics: Implement real-time streaming data ingestion using Fabric Real-Time Hub, KQL Database, andEventstream
Governance & Security: Implement data security, quality checks, and governance principles.
2. Technical Skill Requirements
Core Fabric: Deep knowledge of Microsoft Fabric components:OneLake, Lakehouse, Data Factory, Notebooks, and Data Warehouse.
Azure Data Stack: Proficiency in Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Languages: Strong Python (PySparkPandas/Polars) and SQL skills.
Data Modeling: Expert in dimensional modeling (Star Schema) and DAX for semantic models.
DevOps: Experience with CI/CD for data pipelines and workspace deployment pipelines
3. Qualifications
Experience: 4–6years in data engineering, data warehousing, or analytics engineering.
Certifications: Microsoft Certified: Fabric Data Engineer Associate (DP-700) is highly preferred, replacing the older DP-203
Mandatory skill sets:
Core Fabric: Deep knowledge of Microsoft Fabric components:OneLake, Lakehouse, Data Factory, Notebooks, and Data Warehouse.
Azure Data Stack: Proficiency in Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Languages: Strong Python (PySparkPandas/Polars) and SQL skills.
Data Modeling: Expert in dimensional modeling (Star Schema) and DAX for semantic models.
DevOps: Experience with CI/CD for data pipelines and workspace deployment pipelines
Preferred skill sets:
Core Fabric: Deep knowledge of Microsoft Fabric components:OneLake, Lakehouse, Data Factory, Notebooks, and Data Warehouse.
Azure Data Stack: Proficiency in Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Languages: Strong Python (PySparkPandas/Polars) and SQL skills.
Data Modeling: Expert in dimensional modeling (Star Schema) and DAX for semantic models.
DevOps: Experience with CI/CD for data pipelines and workspace deployment pipelines
Years of Experience required : 4–6years
Education qualification:B.E,B.Tech,M.E,M.Tech, MCA
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Engineering, Master of Business AdministrationDegrees/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
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
March 31, 2026
At PwC, we help clients drive their companies to the leading edge. We’re a tech-forward, people-empowered network with more than 370,000 people in 149 countries. Across audit and assurance, tax and legal, deals and consulting we help build, accelerate and sustain momentum. Find out more at www.pwc.com.
PwC: Audit and assurance, consulting and tax services
PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity. Content on this page has been prepared for general information only and is not intended to be relied upon as accounting, tax or professional advice. Please reach out to your advisors for specific advice.
