Key Skills:
● Strong hands-on experience in Python and Advanced SQL
● Mandatory expertise in Databricks platform and ecosystem
● Experience building scalable ETL pipelines and data ingestion frameworks
● Strong understanding of Lakehouse architecture principles
● Hands-on experience with Unity Catalog
● Experience in data ingestion, transformation, and pipeline optimization
● Exposure to LakeFlow, DBT, and AI/BI Genie
● Strong performance tuning and query optimization skills
● Experience working with large-scale structured and semi-structured datasets
● Good understanding of modern data engineering best practices
● Strong communication and stakeholder management skills
● Ability to independently lead and deliver data engineering initiatives
Responsibilities:
● Design, develop, and maintain scalable data pipelines using Databricks
● Build and optimize ETL/ELT workflows and ingestion frameworks
● Implement modern data architectures using Lakehouse principles
● Perform performance optimization across data pipelines and workloads
● Handle end-to-end ownership from requirement gathering to deployment
● Collaborate with business teams, architects, and cross-functional stakeholders
● Ensure data quality, scalability, reliability, and governance standards
● Stay updated with advancements in Databricks and cloud data technologies
● Support data-driven initiatives and enterprise analytics requirements
Qualification:
● Bachelor’s or Master’s degree in Computer Science, Engineering, or related field