Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Senior Associate
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
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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….
Responsibilities:
- Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services.
- Provide technical leadership and thought leadership as a senior member of the Analytics Practice in areas such as data access & ingestion, data processing, data integration, data modeling, database design & implementation, data visualization, and advanced analytics.
- Engage and collaborate with customers to understand business requirements/use cases and translate them into detailed technical specifications.
- Develop best practices including reusable code, libraries, patterns, and consumable frameworks for cloud-based data warehousing and ETL.
- Maintain best practice standards for the development or cloud-based data warehouse solutioning including naming standards.
- Designing and implementing highly performant data pipelines from multiple sources using Apache Spark and/or Azure Databricks
- Integrating the end-to-end data pipeline to take data from source systems to target data repositories ensuring the quality and consistency of data is always maintained
- Working with other members of the project team to support delivery of additional project components (API interfaces)
- Evaluating the performance and applicability of multiple tools against customer requirements
- Working within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints.
- Integrate Databricks with other technologies (Ingestion tools, Visualization tools).
- Proven experience working as a data engineer
- Highly proficient in using the spark framework (python and/or Scala)
- Extensive knowledge of Data Warehousing concepts, strategies, methodologies.
- Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably in Databricks).
- Hands on experience designing and delivering solutions using Azure including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Cosmos DB, Azure Stream Analytics
- Experience in designing and hands-on development in cloud-based analytics solutions.
- Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required.
- Designing and building of data pipelines using API ingestion and Streaming ingestion methods.
- Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.
- Thorough understanding of Azure Cloud Infrastructure offerings.
- Strong experience in common data warehouse modeling principles including Kimball.
- Working knowledge of Python is desirable
- Experience developing security models.
- Databricks & Azure Big Data Architecture Certification would be plus
Mandatory skill sets:
ADE, ADB, ADF
Preferred skill sets:
ADE, ADB, ADF
Years of experience required:
3-8 Years
Education qualification:
BE, B.Tech, MCA, M.Tech
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Engineering, Master of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Azure Devops
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture Development, 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, Data Pipeline {+ 27 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
April 15, 2026