1 to 25 of 295 Permanent Hadoop Jobs in the UK

open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi. Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka. Experience with workflow orchestration tools like Apache Airflow. Experience with containerisation using Docker and deployment on Kubernetes. Experience with More ❯

S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks. Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation. Experience in working with LLM More ❯

S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks. Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation. Experience in working with LLM More ❯

models and platform products in general. Knowledge of time series analysis and forecasting techniques. Technical Skills: Languages: Python, SQL, R. Big Data: Apache Spark, Hadoop, Kafka, or similar. Timeseries Database: InfluxDB or TimescaleDB, or similar. Cloud Platforms: AWS Redshift, Azure Synapse, or similar. ML/AI Tools: scikit-learn More ❯

Data Analytics - Specialty or AWS Certified Solutions Architect - Associate. Experience with Airflow for workflow orchestration. Exposure to big data frameworks such as Apache Spark, Hadoop, or Presto. Hands-on experience with machine learning pipelines and AI/ML data engineering on AWS. Benefits: Competitive salary and performance-based bonus More ❯

a similar role, with a focus on data infrastructure management Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure). Ideally some programming skills in languages like Python, Java, or Scala More ❯

a team-oriented environment. Preferred Skills: Experience with programming languages such as Python or R for data analysis. Knowledge of big data technologies (e.g., Hadoop, Spark) and data warehousing concepts. Familiarity with cloud data platforms (e.g., Azure, AWS, Google Cloud) is a plus. Certification in BI tools, SQL, or More ❯

large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale More ❯

large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale More ❯

experience in their technologies You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices and design patterns More ❯

Python and R, and ML libraries (TensorFlow, PyTorch, scikit-learn). Hands-on experience with cloud platforms (Azure ML) and big data ecosystems (e.g., Hadoop, Spark). Strong understanding of CI/CD pipelines, DevOps practices, and infrastructure automation. Familiarity with database systems (SQL Server, Snowflake) and API integrations. More ❯

roles, with 5+ years in leadership positions. Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Spark, Kafka, Hadoop). Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. Proven experience in enterprise-level architecture design More ❯

proficiency in data modeling, SQL, NoSQL databases, and data warehousing. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud, and cloud-based data services (e.g., AWS Redshift, Azure Synapse More ❯

with data visualisation tools such as Tableau, Power BI, or visualisation libraries in Python (matplotlib, Seaborn). Experience with big data technologies such as Hadoop, Spark, or distributed computing frameworks. Strong understanding of data preprocessing, feature engineering, and data pipeline development. Bachelor's or Master's degree in Data More ❯

Frameworks: Extensive experience with AI frameworks and libraries, including TensorFlow, PyTorch, or similar. ? Data Processing: Expertise in big data technologies such as Apache Spark, Hadoop, and experience with data pipeline tools like Apache Airflow. ? Cloud Platforms: Strong experience with cloud services, particularly AWS, Azure, or Google Cloud Platform, including More ❯

with programming languages such as Python or Java Understanding of data warehousing concepts and data modeling techniques Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage Excellent problem-solving and analytical skills Strong communication and collaboration skills Benefits Enhanced leave - 38 days inclusive of 8 UK More ❯

with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Benefits Enhanced leave - 38 days inclusive of 8 UK More ❯

modern data architectures, ensuring scalability and performance. Work on data integration, ETL, warehousing, and API development. Deploy and maintain big data technologies such as Hadoop, Spark, and Kafka. Develop data models and visualisation solutions using Power BI, Tableau, or Looker. Ensure compliance with GDPR, CCPA, and data governance policies. More ❯

as MLflow, Kubeflow, TensorFlow Serving, and Seldon for seamless production workflows. Big Data Engineering : Architect high-performance data pipelines using Apache Spark, Kafka ,and Hadoop for real-time and batch processing. Generative AI : Explore and integrate generative technologies, including GPT, DALL-E , and GANs , for innovative applications in user More ❯

MongoDB, Cassandra). • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud). • Expertise in ETL tools and processes (e.g. More ❯

large datasets. Expertise in creating impactful visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI. Familiarity with big data tools and platforms like Hadoop, Spark, or cloud-based tools (e.g., AWS, Google Cloud, Azure). Strong analytical skills with the ability to identify, define, and solve complex business More ❯

large datasets. Expertise in creating impactful visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI. Familiarity with big data tools and platforms like Hadoop, Spark, or cloud-based tools (e.g., AWS, Google Cloud, Azure). Strong analytical skills with the ability to identify, define, and solve complex business More ❯

data modeling, and ETL/ELT processes.* Proficiency in programming languages such as Python, Java, or Scala.* Experience with big data technologies such as Hadoop, Spark, and Kafka.* Familiarity with cloud platforms like AWS, Azure, or Google Cloud.* Excellent problem-solving skills and the ability to think strategically.* Strong More ❯

methodologies. Skill Set & Experience: We are specifically looking for a Scala Data Engineer – not an application developer. The candidate must have experience migrating from Hadoop to the Cloud using Scala . Strong experience in Data Pipeline creation is essential. Candidates should have Big Data experience . Please ensure they More ❯

Proven experience as a Data Engineer with a strong background in data pipelines. Proficiency in Python, Java, or Scala, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with Databricks, Azure AI Services, and cloud platforms (AWS, Google Cloud, Azure). Solid understanding of SQL and NoSQL databases. More ❯