Data Engineers - Databricks - Senior Manager

PwC; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

PwC in Hyderabad is seeking a skilled Data Engineer to lead Databricks-based data engineering workstreams. You will design scalable data pipelines, integration patterns, and transformations to support analytics and reporting needs.

You will develop cloud-native data architectures using Databricks, Azure Data Factory, and Snowflake, ensuring data quality and lineage. Collaborate with stakeholders, guide teams through complex issues, and help deliver reusable frameworks across engagements.

Qualifications

• Databricks platform experience across data engineering projects.
• Experience with cloud data platforms (Azure, AWS, or Snowflake).
• Led client-facing data modernization projects.
• Proficient in designing data pipelines, data modeling, and transformations.
• Ability to mentor teams through ambiguity and solve technical issues.

Responsibilities

• Lead data engineering workstreams for Databricks-based solutions.
• Design scalable data pipelines and integration patterns.
• Develop cloud data architectures using Databricks, Azure Data Factory, Snowflake.
• Validate data quality, lineage, and transformations throughout development.
• Present progress, risks, and options to client leaders.

Skills

Databricks

Data engineering

Data pipelines

Data modeling

Transformation solutions

Mentoring

Client-facing delivery

Education

MIS / Computer Science or related field

Tools

Azure

AWS

Snowflake

Job description

Responsibilities

• Leading data engineering workstreams for Databricks-based client solutions across data modernization initiatives
• Designing and building scalable data pipelines, integration patterns, and transformation logic to support analytics and reporting needs
• Developing cloud-based data architectures using Databricks, Azure Data Factory, Snowflake, and related platforms
• Applying data modeling, warehouse design, and performance tuning methods to improve data availability and query response times
• Coordinating technical delivery across teams and stakeholders to translate business requirements into data solutions
• Validating data quality, lineage, and transformation logic throughout the development lifecycle
• Guiding teams through complex implementation issues, tradeoffs, and dependencies across multiple workstreams
• Coaching team members on data engineering methods, delivery planning, and technical problem solving
• Presenting progress, risks, and solution options to client leaders in a clear and concise manner
• Supporting the development of reusable frameworks and delivery approaches that improve efficiency across engagements

What Sets You Apart

• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
• Demonstrating Databricks platform experience across data engineering projects
• Applying cloud data platform knowledge with Azure, AWS, or Snowflake
• Leading client-facing data modernization work through complex delivery
• Crafting data pipelines, modeling, and transformation solutions
• Coaching teams through ambiguity while solving technical issues