Azure Databricks Data Engineer| 9 to 12 Years| Gyansys | Hybrid - PradeepIT Consulting Services Pvt Ltd | Career Page

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Azure Databricks Data Engineer| 9 to 12 Years| Gyansys | Hybrid

Bangalore, Karnataka, India

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Job Openings Azure Databricks Data Engineer| 9 to 12 Years| Gyansys | Hybrid

About the job Azure Databricks Data Engineer| 9 to 12 Years| Gyansys | Hybrid

Job Description: Data Engineer (Azure Databricks & PySpark)

Position: Data Engineer**
Experience:** 9 to 12 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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Azure Databricks Data Engineer

Description