Data Engineer
Posted Updated
Please find the below JD for Data Engineering.
Position:
Data Engineer Experience:
4 to 10 Years experience in PySpark and Data bricks Location :
Hyderabad Overview: In this role candidate will be responsible for understanding complex data sets, managing multiple disparate data sources, and implementing strong validation processes to ensure data quality. The ideal candidate will have a strong background in python, ETL, pyspark, spark, sql, Amazon Web Services, and Databricks. Experience in Tableau is a plus. Responsibilities: Develop and maintain ETL pipelines to support data processing, analytics, and visualization needs. Analyze large, complex data sets to identify patterns, trends, and insights. Collaborate with cross-functional teams to understand business requirements and provide data- driven solutions. Manage multiple disparate data sources and integrate them into a cohesive data platform and dashboards. Develop and implement validation processes to ensure data accuracy and consistency. Utilize pyspark, spark, sql, and Databricks to optimize data processing and querying performance.
Position:
Data Engineer Experience:
4 to 10 Years experience in PySpark and Data bricks Location :
Hyderabad Overview: In this role candidate will be responsible for understanding complex data sets, managing multiple disparate data sources, and implementing strong validation processes to ensure data quality. The ideal candidate will have a strong background in python, ETL, pyspark, spark, sql, Amazon Web Services, and Databricks. Experience in Tableau is a plus. Responsibilities: Develop and maintain ETL pipelines to support data processing, analytics, and visualization needs. Analyze large, complex data sets to identify patterns, trends, and insights. Collaborate with cross-functional teams to understand business requirements and provide data- driven solutions. Manage multiple disparate data sources and integrate them into a cohesive data platform and dashboards. Develop and implement validation processes to ensure data accuracy and consistency. Utilize pyspark, spark, sql, and Databricks to optimize data processing and querying performance.