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 transparent 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

📌 Data Engineers - Databricks - Senior Manager (Hyderabad)
🏢 PwC
📍 Hyderabad