16 of 16 Part-Time Apache Spark Jobs in the UK

Django, Docker \n Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo \n Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. \n Data acquisition and development of data sets and improving data quality \n Preparing data for predictive and prescriptive modelling ...

Java or Scala, and SQL. \n Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). \n Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. \n Experience working with cloud ...

Java or Scala, and SQL. \n Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). \n Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. \n Experience working with cloud ...

Django, Docker \n Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo \n Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. \n Data acquisition and development of data sets and improving data quality \n Preparing data for predictive and prescriptive modelling ...

able to guide how one could deploy infrastructure into different environments. \n Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop. \n Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes ...

with proficiency in SQL. \n Experience building data platforms on cloud services like Databricks on Azure or GCP BigQuery and big data technologies like Spark, Flink etc. \n Solid grasp of Kubernetes, CI/CD and Terraform. \n Working knowledge of ETL and ELT frameworks and orchestration tools like ...

Owning the cloud infrastructure underpinning data systems through a DevOps approach \n Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop \n Good understanding of the possible architectures involved in modern data system design (e.g. Data Warehouse, Data Lakes ...

improve overall operational stability of software applications and systems \n Designs and implements data pipelines, analytics workflows, and reporting solutions using Python, Databricks, and Spark \n Develops and maintains web-based applications and dashboards using modern web stacks (React, Angular, etc.) \n Builds and optimises data models, ETL/ ...

houses and data mesh \n Strong understanding of best practice DataOps and MLOps \n Up-to-date understanding of various data engineering technologies including Apache Spark, Databricks and Hadoop \n Strong understanding of agile ways of working \n Up-to-date understanding of various programming languages including Python ...

programming languages like Python or Java along with proficiency in SQL \n Experience working with cloud platforms (e.g., Azure) and big data technologies like Spark, Flink etc., \n Solid grasp of Kubernetes, CI/CD and Terraform \n Working knowledge of ETL and ELT frameworks and orchestration tools like ...

problem-solving skills to collaborate across global teams and translate complex data insights into actionable outputs \n Familiarity with data platforms such as Databricks, Spark, Snowflake, or similar technologies \n Ability to communicate technical concepts clearly to non‐technical stakeholders \n Basic understanding of artificial intelligence concepts, with curiosity ...

Build and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observability \n Develop and operate workflow orchestration (e.g., Apache Airflow) to schedule, monitor, and manage data movement and transformations \n Model and transform data for analytics using SQL and dbt to support business intelligence … data processing and performance tuning \n Hands-on experience with modern data warehousing/lakehouse technologies (e.g., Redshift, BigQuery, Snowflake; and engines such as Spark, Flink, or Trino; and table formats such as Iceberg, Hudi, or similar) \n Strong SQL skills and experience with SQL-based transformation tooling (e.g. ...

digital landscape. This role requires strong expertise in building and managing data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. The successful candidate will design, implement, and maintain scalable, secure data solutions, ensuring compliance with strict security standards and regulations. This is a UK based onsite … role will include: \n \n Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. \n Implement data ingestion, transformation, and integration processes, ensuring data quality and security. \n Collaborate with data architects and security teams to ensure compliance with ...

maintain operational continuity and quality output \n Knowledge of data processing frameworks, including ETL pipelines, data integration, and data modeling (experience with Databricks or Spark preferred) \n Strong analytical and problem-solving skills with the ability to communicate clearly to both technical and non-technical stakeholders \n Basic understanding ...

operate batch and streaming data pipelines with strong scalability, performance, and fault tolerance \n Develop and manage workflow orchestration using tools such as Apache Airflow to support reliable, observable, and well-scheduled data movement and transformations \n Implement and optimize data models and warehouse structures to support analytics … data infrastructure \n\n Preferred qualifications, capabilities, and skills \n \n Data modeling skills \n Experience with data streaming and scalable processing frameworks (e.g., Spark, Flink, Beam, or similar) \n Experience automating deployment, releases, and testing in continuous integration and continuous delivery pipelines \n Experience with lakehouse patterns ...

qualifications, capabilities, and skills \n \n Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray) \n Experience of big data technologies (e.g. Spark, Hadoop) \n Have constructed batch and streaming microservices exposed as REST/gRPC endpoints \n Familiarity with GraphQL \n\n #CIBAppliedAI \n ABOUT ...