

Hadoop Engineer - ODP Platform
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Hadoop Engineer - ODP Platform, hybrid working in Birmingham/Sheffield, with a contract until 28/11/2025. Pay rate is competitive. Requires 5+ years in Hadoop, strong Python and Apache Airflow skills, and on-premises experience.
π - Country
United Kingdom
π± - Currency
Β£ GBP
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π° - Day rate
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ποΈ - Date discovered
August 12, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
West Midlands, England, United Kingdom
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π§ - Skills detailed
#Deployment #HDFS (Hadoop Distributed File System) #Python #Compliance #Storage #Shell Scripting #Data Governance #Programming #Scripting #Spark (Apache Spark) #Logging #Linux #YARN (Yet Another Resource Negotiator) #HBase #Ansible #Automation #Apache Airflow #Data Processing #Airflow #Puppet #Data Engineering #Hadoop #"ETL (Extract #Transform #Load)" #Scala #Data Pipeline #Data Security #Security #Monitoring
Role description
Role Title: Hadoop Engineer / ODP Platform
Location: Birmingham / Sheffield - Hybrid working with 3 days onsite per week
End Date: 28/11/2025
Role Overview
We are seeking a highly skilled Hadoop Engineer to support and enhance our Operational Data Platform (ODP) deployed in an on-premises environment.
The ideal candidate will have extensive experience in the Hadoop ecosystem, strong programming skills, and a solid understanding of infrastructure-level data analytics. This role focuses on building and maintaining scalable, secure, and high-performance data pipelines within enterprise-grade on-prem systems.
Key Responsibilities
β’ Design, develop, and maintain data pipelines using Hadoop technologies in an on-premises infrastructure.
β’ Build and optimise workflows using Apache Airflow and Spark Streaming for real-time data processing.
β’ Develop robust data engineering solutions using Python for automation and transformation.
β’ Collaborate with infrastructure and analytics teams to support operational data use cases.
β’ Monitor and troubleshoot data jobs, ensuring reliability and performance across the platform.
β’ Ensure compliance with enterprise security and data governance standards.
Required Skills & Experience
β’ Minimum 5 years of experience in Hadoop and data engineering.
β’ Strong hands-on experience with Python, Apache Airflow, and Spark Streaming.
β’ Deep understanding of Hadoop components (HDFS, Hive, HBase, YARN) in on-prem environments.
β’ Exposure to data analytics, preferably involving infrastructure or operational data.
β’ Experience working with Linux systems, shell scripting, and enterprise-grade deployment tools.
β’ Familiarity with monitoring and logging tools relevant to on-prem setups.
Preferred Qualifications
β’ Experience with enterprise ODP platforms or similar large-scale data systems.
β’ Knowledge of configuration management tools (e.g., Ansible, Puppet) and CI/CD in on-prem environments.
β’ Understanding of network and storage architecture in data centers.
β’ Familiarity with data security, compliance, and audit requirements in regulated industries.
Role Title: Hadoop Engineer / ODP Platform
Location: Birmingham / Sheffield - Hybrid working with 3 days onsite per week
End Date: 28/11/2025
Role Overview
We are seeking a highly skilled Hadoop Engineer to support and enhance our Operational Data Platform (ODP) deployed in an on-premises environment.
The ideal candidate will have extensive experience in the Hadoop ecosystem, strong programming skills, and a solid understanding of infrastructure-level data analytics. This role focuses on building and maintaining scalable, secure, and high-performance data pipelines within enterprise-grade on-prem systems.
Key Responsibilities
β’ Design, develop, and maintain data pipelines using Hadoop technologies in an on-premises infrastructure.
β’ Build and optimise workflows using Apache Airflow and Spark Streaming for real-time data processing.
β’ Develop robust data engineering solutions using Python for automation and transformation.
β’ Collaborate with infrastructure and analytics teams to support operational data use cases.
β’ Monitor and troubleshoot data jobs, ensuring reliability and performance across the platform.
β’ Ensure compliance with enterprise security and data governance standards.
Required Skills & Experience
β’ Minimum 5 years of experience in Hadoop and data engineering.
β’ Strong hands-on experience with Python, Apache Airflow, and Spark Streaming.
β’ Deep understanding of Hadoop components (HDFS, Hive, HBase, YARN) in on-prem environments.
β’ Exposure to data analytics, preferably involving infrastructure or operational data.
β’ Experience working with Linux systems, shell scripting, and enterprise-grade deployment tools.
β’ Familiarity with monitoring and logging tools relevant to on-prem setups.
Preferred Qualifications
β’ Experience with enterprise ODP platforms or similar large-scale data systems.
β’ Knowledge of configuration management tools (e.g., Ansible, Puppet) and CI/CD in on-prem environments.
β’ Understanding of network and storage architecture in data centers.
β’ Familiarity with data security, compliance, and audit requirements in regulated industries.