Role & Responsibilities Overview:

 Develop and optimize ETL pipelines from various data sources using Databricks on cloud (AWS, Azure,etc.)

 Experienced in implementing standardized pipelines with automated testing, Airflow scheduling, Azure DevOps for CI/CD, Terraform for infrastructure as code, and Splunk for monitoring

 Continuously improve systems through performance enhancements and cost reductions in compute and storage

 Data Processing and API Integration: Utilize Spark Structured Streaming for real-time data processing and integrate data outputs with REST APIs

 Lead Data Engineering Projects to manage and implement data-driven communication systems

 Experienced with Scrum and Agile Methodologies to coordinate global delivery teams, run scrum ceremonies, manage backlog items, and handle escalations

 Integrate data across different systems and platforms

 Strong verbal and written communication skills to manage client discussions

Candidate Profile:

 8 years experience in developing and implementing ETL pipelines from various data sources using Databricks on cloud

 Based out of US

 Some experience in insurance domain/ data is must

 Programming Languages – SQL, Python

 Technologies - IaaS (AWS or Azure or GCP), Databricks platform, Delta Lake storage, Spark (PySpark, Spark SQL).

o Good to have - Airflow, Splunk, Kubernetes, Power BI, Git, Azure Devops

 Project Management using Agile, Scrum

 B.S. Degree in a data-centric field (Mathematics, Economics, Computer Science, Engineering or other science field), Information Systems, Information Processing or engineering.

 Excellent communication & leadership skills, with the ability to lead and motivate team members