Migration and Implementation: Lead the migration of legacy Java-based data pipelines to Databricks; design and maintain scalable data pipelines using Databricks and Spark
Data Engineering and Management: Create, maintain, and update data models; build infrastructure for optimal data extraction, transformation, and loading (ETL)
Performance Analysis and Optimization: Analyse and optimize Databricks jobs and queries; monitor and tune Databricks environments for scalability and reliability. Address data-related technical issues; assist teams with data transformation workloads; perform root cause analysis to identify improvement opportunities
Technical Improvement: Implement best practices for efficient data processing and storage; develop processes that support data transformation, workload management, data structures, and metadata
Technical Mentorship: Mentor a team of data engineers; serve as the go-to person for Databricks-related queries; conduct Proof of Concepts (POCs) to demonstrate Databricks capabilities
Required Experience
Proficiency in Python / PySpark
Proven experience with Databricks and Spark, including building and optimizing data pipelines
Strong data modelling experience and advanced SQL knowledge
Experience with Delta Lake and performance analysis in Databricks
Knowledge of message queuing, stream processing, and scalable big data stores
Experience with Talend is preferable
Non-Technical / Behavioral Competencies required
Must have worked with US based clients in onsite/off shore delivery model
Strong verbal and written communication, technical articulation, listening, and presentation skills are essential
Should have proven analytical and problem-solving skills
Demonstrated expertise in prioritization, time management, and stakeholder management (both internal and external) is necessary
Should be a quick learner, self-starter, proactive, and an effective team player
Must have experience working under tight deadlines within a matrix organizational structure