KPMG India

Data Engineer

25 September 2024
Full Time
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Deadline date:
£49000 - £92000 / year

Job Description

Mandatory Skills

 

  • At least 2 -4   years of consulting or client service delivery experience on Azure
  • At least 2 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases such as MySQL and data warehouse solutions such as Snowflake
  • Extensive experience providing practical direction within the Azure Native services and Hadoop
  • Extensive hands-on experience implementing data ingestion, ETL and data processing using Azure services: ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks, Azure Data Catalog, Cosmo DB etc.
  • Minimum of 3 years of hands-on experience in Azure and Big Data technologies such as Python, SQL, ADLS/Blob, Spark/SparkSQL, Databricks, Hive and streaming technologies such as Kafka, EventHub, NiFi etc.
  • Must be Well versed with Pyspark development on databricks.
  • Well versed in DevSecOps and CI/CD deployments
  • Cloud migration methodologies and processes including tools like Azure Data Factory, Data Migration Service, Event Hub, Kafka, etc.
  • Minimum of 2 years of RDBMS experience
  • Experience in using Big Data File Formats and compression techniques
  • Experience working with Developer tools such as Azure DevOps, Visual Studio Team Server, Git, Jenkins, etc.
  • Experience with private and public cloud architectures, pros/cons, and migration considerations.
  • Bachelors or higher degree in Computer Science or a related discipline; or equivalent (minimum 2 years work experience). If Associate’s Degree, must have equivalent minimum 2 years work experience

 

Primary Roles and Responsibilities 

 

An Azure Data Engineer is responsible for designing, building, and maintaining the data infrastructure for an organization using Azure cloud services. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The Azure Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency. 

Preferred Skills

  • DevOps on an Azure platform
  • Experience developing and deploying ETL solutions on Azure
  • IoT, event-driven, microservices, Containers/Kubernetes in the cloud
  • Familiarity with the technology stack available in the industry for metadata management:  Data Governance, Data Quality, MDM, Lineage, Data Catalog etc.
  • Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation:  Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
  • Multi-cloud experience a plus – Azure, AWS, Google

 

  • At least 2 -4   years of consulting or client service delivery experience on Azure
  • At least 2 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases such as MySQL and data warehouse solutions such as Snowflake
  • Extensive experience providing practical direction within the Azure Native services and Hadoop
  • Extensive hands-on experience implementing data ingestion, ETL and data processing using Azure services: ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks, Azure Data Catalog, Cosmo DB etc.
  • Minimum of 3 years of hands-on experience in Azure and Big Data technologies such as Python, SQL, ADLS/Blob, Spark/SparkSQL, Databricks, Hive and streaming technologies such as Kafka, EventHub, NiFi etc.
  • Must be Well versed with Pyspark development on databricks.
  • Well versed in DevSecOps and CI/CD deployments
  • Cloud migration methodologies and processes including tools like Azure Data Factory, Data Migration Service, Event Hub, Kafka, etc.
  • Minimum of 2 years of RDBMS experience
  • Experience in using Big Data File Formats and compression techniques
  • Experience working with Developer tools such as Azure DevOps, Visual Studio Team Server, Git, Jenkins, etc.
  • Experience with private and public cloud architectures, pros/cons, and migration considerations.
  • Bachelors or higher degree in Computer Science or a related discipline; or equivalent (minimum 2 years work experience). If Associate’s Degree, must have equivalent minimum 2 years work experience

 

Primary Roles and Responsibilities 

 

An Azure Data Engineer is responsible for designing, building, and maintaining the data infrastructure for an organization using Azure cloud services. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The Azure Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency. 

Preferred Skills

  • DevOps on an Azure platform
  • Experience developing and deploying ETL solutions on Azure
  • IoT, event-driven, microservices, Containers/Kubernetes in the cloud
  • Familiarity with the technology stack available in the industry for metadata management:  Data Governance, Data Quality, MDM, Lineage, Data Catalog etc.
  • Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation:  Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
  • Multi-cloud experience a plus – Azure, AWS, Google

 

  • At least 2 -4   years of consulting or client service delivery experience on Azure
  • At least 2 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases such as MySQL and data warehouse solutions such as Snowflake
  • Extensive experience providing practical direction within the Azure Native services and Hadoop
  • Extensive hands-on experience implementing data ingestion, ETL and data processing using Azure services: ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks, Azure Data Catalog, Cosmo DB etc.
  • Minimum of 3 years of hands-on experience in Azure and Big Data technologies such as Python, SQL, ADLS/Blob, Spark/SparkSQL, Databricks, Hive and streaming technologies such as Kafka, EventHub, NiFi etc.
  • Must be Well versed with Pyspark development on databricks.
  • Well versed in DevSecOps and CI/CD deployments
  • Cloud migration methodologies and processes including tools like Azure Data Factory, Data Migration Service, Event Hub, Kafka, etc.
  • Minimum of 2 years of RDBMS experience
  • Experience in using Big Data File Formats and compression techniques
  • Experience working with Developer tools such as Azure DevOps, Visual Studio Team Server, Git, Jenkins, etc.
  • Experience with private and public cloud architectures, pros/cons, and migration considerations.
  • Bachelors or higher degree in Computer Science or a related discipline; or equivalent (minimum 2 years work experience). If Associate’s Degree, must have equivalent minimum 2 years work experience

 

Primary Roles and Responsibilities 

 

An Azure Data Engineer is responsible for designing, building, and maintaining the data infrastructure for an organization using Azure cloud services. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The Azure Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency. 

Preferred Skills

  • DevOps on an Azure platform
  • Experience developing and deploying ETL solutions on Azure
  • IoT, event-driven, microservices, Containers/Kubernetes in the cloud
  • Familiarity with the technology stack available in the industry for metadata management:  Data Governance, Data Quality, MDM, Lineage, Data Catalog etc.
  • Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation:  Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
  • Multi-cloud experience a plus – Azure, AWS, Google

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