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Azure Databricks Data Engineer| 6 to 8 Years| Gyansys | Hybrid - PradeepIT Consulting Services Pvt Ltd | Career Page
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Azure Databricks Data Engineer| 6 to 8 Years| Gyansys | Hybrid
Bangalore, Karnataka, India
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Job Openings Azure Databricks Data Engineer| 6 to 8 Years| Gyansys | Hybrid
About the job Azure Databricks Data Engineer| 6 to 8 Years| Gyansys | Hybrid
Job Description: Data Engineer (Azure Databricks & PySpark)
Position: Data Engineer**
Experience:** 6 to 8 years **
Primary Skills:** Azure Databricks, PySpark, SQL (M)**
Secondary Skills**: ADF (Azure Data Factory) (M)**
Project Exposure:** Cloud migration (M)Location: Bengaluru/HyderabadMode of Work: HybridSalary : 13 lac to 17 lacNotice Period: 15 to 30 Days (M)
Databricks Engineer Job Description
Responsibilities:
- Work as part of a global distribution team to design and implement Hadoop big data solutions in alignment with business needs and project schedules.
- 5+ years of data warehousing/engineering, software solutions design, and development experience.
- Code, test, and document new or modified data systems to create robust and scalable applications for data analytics.
- Work with other Big Data developers to make sure that all data solutions are consistent.
- Partner with the business community to understand requirements, determine training needs, and deliver user training sessions.
- Perform technology and product research to better define requirements, resolve important issues, and improve the overall capability of the analytics technology stack.
- Evaluate and provide feedback on future technologies and new releases/upgrades.
- Support Big Data and batch/real-time analytical solutions leveraging transformational technologies.
- Work on multiple projects as a technical team member or drive:
- User requirement analysis and elaboration
- Design and development of software applications
- Testing and build automation tools
- Research and incubate new technologies and frameworks.
- Experience with agile or other rapid application development methodologies and tools like Bitbucket, Jira, and Confluence.
- Have built solutions with public cloud providers such as AWS, Azure, or GCP.
Expertise Required:
- Hands-on experience in Databricks stack
- Data Engineering technologies (Ex: Spark, Hadoop, Kafka, etc.)
- Proficiency in Streaming technologies
- Hands-on experience in Python and SQL
- Expertise in implementing Data Warehousing solutions
- Expertise in any ETL tool (e.g., SSIS, Redwood)
- Good understanding of submitting jobs using Workflows, API & CLI
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