IN_Senior Associate_Azure DE_Advisory_Hyderabad 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: Utilize PySpark , 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 and OneLake to manage data without moving it. Real-time Analytics: Implement real-time streaming data ingestion using Fabric Real-Time Hub, KQL Database, and Eventstream . 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 ( PySpark /Pandas/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 – 6 years 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 ( PySpark /Pandas/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: Robust Python ( PySpark /Pandas/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 – 6 years 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 Experience Level Senior Level

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