Onsite
Full Time Software Architecture & Engineering
Responsibilities
Develop modern data solutions and architecture for cloud-native data platforms.
Build cost-effective infrastructure in Databricks and orchestrate workflows using Databricks/ADF.
Lead data strategy sessions focused on scalability, performance, and flexibility.
Collaborate with customers to implement solutions for data modernization.
Create training plans and learning materials to upskill VM associates.
Build a smart operations framework for DataOps and MLOps.
Requirements
Should have 14+ years of experience with last 4 years in implementing Cloud native end-to-end Data Solutions in Databricks from ingestion to consumption to support variety of needs such as Modern Data warehouse, BI, Insights and Analytics
Experience in architecture and implementing End to End Modern Data Solutions using Azure and advanced data processing frameworks like Databricks
Experience with Databricks, PySpark, and modern data platforms.
Proficiency in cloud-native architecture and data governance.
Strong experience in migrating from on-premises to cloud solutions (Spark, Hadoop to Databricks).
Understanding of Agile/Scrum methodologies.
Demonstrated knowledge of data warehouse concepts. Strong understanding of cloud-native databases, columnar database architectures.
Ability to work with Data Engineering teams, Data Management Team, BI and Analytics in a complex development IT environment.
Good appreciation and at least one implementation experience on processing substrates in Data Engineering - such as ETL Tools, Kafka, ELT techniques
Data Mesh and Data Products designing, and implementation knowledge will be an added advantage.