This position requires a proven track record of transforming processes, driving customer value, cost savings with experience in running end-to-end analytics for large-scale organizations.
Design, build, and maintain scalable data pipelines to support analytics, reporting, and advanced modeling needs.
Collaborate with consultants, analysts, and clients to understand data requirements and translate them into effective data solutions.
Ensure data accuracy, quality, and integrity through validation, cleansing, and transformation processes.
Develop and optimize data models, ETL workflows, and database architectures across cloud and on-premises environments.
Support data-driven decision-making by delivering reliable, well-structured datasets and enabling self-service analytics.
Provides seamless integration with cloud platforms (Azure), making it easy to build and deploy end-to-end data pipelines in the cloud
Scalable clusters for handling large datasets and complex computations in Databricks, optimizing performance and cost management. Must to have 1.
Client Engagement
Experience and collaboration with cross-functional teams
Data Engineering background in Databricks
Capable of working effectively as an individual contributor or in cooperative team environments
Effective communication and thought leadership with proven record.
Candidate Profile
Bachelors/masters degree in economics, mathematics, computer science/engineering, operations research or related analytics areas
3+ years experience must be in Data engineering.
Hands on experience on SQL, Python, Databricks, cloud Platform like Azure etc.
Prior experience in managing and delivering end to end projects
Outstanding written and verbal communication skills
Able to work in quick pace continuously evolving setting and ready to take up uphill challenges
Is able to understand cross cultural differences and can work with clients across the globe.