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profile Job Location:

Delhi - India

profile Monthly Salary: Not Disclosed
Posted on: 6 hours ago
Vacancies: 1 Vacancy

Job Summary

Databricks Unified Data Analytics Platform - 137237

As a Data Engineer you will design develop and maintain data solutions that facilitate data generation collection and processing. Your typical day will involve creating data pipelines ensuring data quality and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and deliver effective solutions that meet business needs.

Roles & Responsibilities:
  • Expected to be an SME.
  • Collaborate and manage the team to perform.
  • Responsible for team decisions.
  • Engage with multiple teams and contribute on key decisions.
  • Provide solutions to problems for their immediate team and across multiple teams.
  • Mentor junior team members to enhance their skills and knowledge.
  • Continuously evaluate and improve data processes to enhance efficiency.

Professional & Technical Skills:
  • Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.
  • Good To Have Skills: Experience with PySpark Microsoft Azure Data Services Microsoft Azure Databricks.
  • Strong understanding of data pipeline architecture and design.
  • Experience with data quality frameworks and best practices.
  • Familiarity with ETL tools and methodologies.

Additional Information:
  • The candidate should have minimum 5 years of experience in Databricks Unified Data Analytics Platform.
  • This position is based at our Bengaluru office.
  • A 15 years full time education is required.
Databricks Unified Data Analytics Platform - 137237 As a Data Engineer you will design develop and maintain data solutions that facilitate data generation collection and processing. Your typical day will involve creating data pipelines ensuring data quality and implementing ETL processes to migrate...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala