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Databricks Architect
4 months ago
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).
- 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
- Ability to work independently with some level of ambiguity and juggle multiple demands