
Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Manager
& 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.
& 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 organisationstokeep 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:
About the Role:
We are hiring sharp, hands-on Data Architect to lead the design and implementation of scalable, high-performance data solutionsacross both traditional and cloud-based data platforms.This role demands deep expertise in PySpark, SQL, Pythonand Data Modelling, along with a strong understanding of cloud platforms and modern data engineering practices
What you will do:
Architect,Designand implement scalable end-end data solutions, ensuring scalability, performance, and cost-efficiency
Build and Deploy batch and near real-time use casesincloud environments
DevelopmentusingPysparkand Pythonscripts for large-scale data processing and ETL workflows
Write optimized, complex SQL for data transformation and analysis
Optimize existing Pyspark and SQLscripts over large-scale datasets (TBs) with a focus on performance and cost-efficiency
Create and maintain data models, ensuring data quality and consistency
Leverage AI/ML modelsindata transformations and analytics.
Implement data governance and security best practices in cloud environments
Collaborate across teams to translate business requirements into robust technical solutions
Mandatory skill sets:
‘Must have’Primaryskills and experiences
7+ years of hands-on experience in Data Engineering
Strong command over SQL, Python, and PySparkfor data manipulation and analysis
Deep experience with data& analytics & warehousingand implementation in cloud environments (AzureAWS)
Proficiency in data modeling techniques for cloud-based systems (Databricks, Snowflake)
Solid understanding of ETL/ELT processes and best practices in cloud architectures
Experience with dimensional modeling, star schemas, and data mart design
Performance optimization techniques for cloud-based data warehouses
Strong analytical thinking and problem-solving skills
Secondary Skills:
Airflow (Workflow Design and Orchestration)
Apache Kafka – real-time streaming
CI/CD (Automation,GitOps, DevOps for Data)
Understanding of warehousing tools like Teradata, Netezza, etc.
Preferred skill sets:
‘Good to have’ knowledge, skills and experiences
Familiarity with data lake architectures and delta lake concepts
Data Warehouse experience usingDatabricks/Snowflake
Knowledge of data warehouse migration strategies to cloud
Experience with real-time data streaming technologies (e.g., Apache Kafka, Azure Event Hubs)
Exposure to data quality and data governance tools and methodologies
Understanding of
Certifications in Azure orAWSor Databricks
Years of experience required:
Experience
7-10years
Certifications
SparkCertified
DatabricksDE Associate/Professional Certified
Good to Have
Snowflake SnowProCoreCertified
Education qualification:
BE,B.Tech, ME,M,Tech, MBA, MCA (60% above)
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Engineering, Bachelor of EngineeringDegrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Structured Query Language (SQL)
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
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
May 18, 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.
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