IN_Manager_Data Architect_Data and Analytics_Advisory_Bangalore

At PwC, data and analytics engineers design and develop robust data solutions, transforming raw data into actionable insights for informed decision-making and business growth. This role focuses on building data infrastructure, systems, pipelines, and integration solutions. A career in Data and Analytics services helps organizations uncover enterprise insights, drive business results, and innovate using smarter data analytics, business intelligence, data management, and data assurance.

Must Have

• 8+ years hands-on Data Engineering experience
• Strong SQL, Python, PySpark for data manipulation and analysis
• Deep experience with cloud data warehousing (Azure/AWS)
• Proficiency in data modeling for cloud systems (Databricks, Snowflake)
• Solid understanding of ETL/ELT processes and cloud architectures
• Experience with dimensional modeling, star schemas, data mart design
• Strong analytical thinking and problem-solving skills

Good to Have

• Familiarity with data lake and delta lake concepts
• Familiarity with Snowflake/Databricks Data Warehouse
• Knowledge of cloud data warehouse migration strategies
• Experience with real-time data streaming (Kafka, Azure Event Hubs)
• Exposure to data quality and governance tools
• Understanding of data virtualization and federated query engines
• Understanding of performance optimization for cloud data warehouses
• Apache Airflow for workflow orchestration
• Certifications in Azure, AWS, or Databricks

Perks & Benefits

• Inclusive benefits
• Flexibility programmes
• Mentorship
• Support your wellbeing
• Reward your contributions

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.

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 organisations to keep 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 solutions across both traditional and cloud-based data platforms. This role demands deep expertise in PySpark, SQL, Python and Data Modelling, along with a strong understanding of cloud platforms and modern data engineering practices

What you will do:

• Design and implement scalable data pipelines for batch and near real-time use cases in cloud environments
• Write optimized, complex SQL queries for data transformation and analysis in cloud data warehouses
• Develop efficient Python and PySpark scripts for large-scale data processing and ETL workflows
• Create and maintain data models in Databricks, ensuring data quality and consistency
• Optimize queries and scripts over large-scale datasets (TBs) with a focus on performance and cost-efficiency
• 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’ knowledge, skills and experiences

• 8+ years of hands-on experience in Data Engineering
• Strong command over SQL, Python, and PySpark for data manipulation and analysis
• Deep experience with data warehousing concepts and implementation in cloud environments (Azure/AWS)
• 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
• Strong analytical thinking and problem-solving skills

Preferred skill sets:

‘Good to have’ knowledge, skills and experiences

• Familiarity with data lake architectures and delta lake concepts
• Familiarity with Snowflake/Databricks Data Warehouse
• 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 data virtualization and federated query engines
• Understanding of performance optimization techniques for cloud-based data warehouses
• Apache Airflow – Workflow orchestration and scheduling
• Certifications in Azure or AWS or Databricks

Years of experience required:

• 8-12 years

Education qualification:

• BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)

Education:

Degrees/Field of Study required: Bachelor of Engineering, MBA (Master of Business Administration), Bachelor of Technology

Required Skills:

Data Architecture