Description

  • Bachelor’s degree in Computer Science, Computer Engineering, or related technical discipline.
  • Worked in ETL project for 4-5 years
  • Azure Data Factory (ADF): Candidate should know how to create data pipelines, schedule activities, and manage data movement and transformation using ADF
  • Azure Databricks: Candidate should be adept at using Databricks for data engineering tasks like data ingestion, transformation, and analysis
  • Oracle Database- Candidate should be proficient in using it for data storage, retrieval, and basic manipulation.
  • Very strong in SQL programming
  • Programming in Python / PySpark
  • Azure DevOps: Knowledge of Azure DevOps is valuable for implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines for data engineering solutions
  • Monitoring and Optimization: Understanding how to monitor the performance of data engineering solutions and optimize them for better efficiency is crucial
  • Data Quality and Data Cleaning: Knowing how to ensure data quality and perform data cleaning operations to maintain reliable data is important for data engineers.
  • Data Modeling and ETL/ELT: You should be skilled in data modeling techniques and Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes for data integration.
  • Good to have Apache Hive: Knowledge of Hive, a data warehousing and SQL-like query language that provides an abstraction over Hadoop MapReduce
  • Good to have Apache Spark: Understanding of Spark and its various component

Key Skills
Education

Bachelor's degree

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