1 to 25 of 54 Remote Apache Spark Jobs in the UK

supporting multi-tenant SaaS data platforms with strategies for data partitioning, tenant isolation, and cost management Exposure to real-time data processing technologies such as Kafka, Kinesis, Flink, or Spark Streaming, alongside batch processing capabilities Strong knowledge of SaaS compliance practices and security frameworks Core Competencies Excellent problem-solving abilities with the capacity to translate requirements into production-grade More ❯

a Senior Data Engineer, Tech Lead, Data Engineering Manager etc. Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Experience building, defining, and owning data models, data lakes, and data warehouses Programming proficiency in Python, Pyspark, Scala or Java. Experience operating More ❯

/medical devices preferred but not required) Strong Python programming and data engineering skills (Pandas, PySpark, Dask) Proficiency with databases (SQL/NoSQL), ETL processes, and modern data frameworks (Apache Spark, Airflow, Kafka) Solid experience with cloud platforms (AWS, GCP, or Azure) and CI/CD for data pipelines Understanding of data privacy and healthcare compliance (GDPR, HIPAA More ❯

databases (SQL Server, MySQL) and NoSQL solutions (MongoDB, Cassandra) Hands-on knowledge of AWS S3 and associated big data services Extensive experience with big data technologies including Hadoop and Spark for large-scale dataset processing Deep understanding of data security frameworks, encryption protocols, access management and regulatory compliance Proven track record building automated, scalable ETL frameworks and data pipeline More ❯

Passion for data with extensive knowledge and experience in Machine Learning techniques. Expertise in key technologies related to Data Management. Proficiency in Python is required; knowledge of SQL and Spark is a plus. Experience with Cloud platforms, specifically Azure and Databricks. In-depth knowledge and experience in Data Analytics Architecture. Understanding of Data Governance processes and platforms. Experience with More ❯

you require: Degree Qualification in Computer Science, Engineering or related field Proven experience as a Data Engineer Strong proficiency in Python and experience with data manipulation frameworks such as Apache Spark In-depth knowledge of relational and non-relational databases, data modelling, and SQL Experience with cloud platforms including Azure Synapse and Fabric Proficiency in designing and implementing More ❯

we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in an agile environment Here’s a taste of More ❯

we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in an agile environment Here’s a taste of More ❯

e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or professional More ❯

e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or professional More ❯

e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or professional More ❯

exposure to cloud-native data infrastructures (Databricks, Snowflake) especially in AWS environments is a plus Experience in building and maintaining batch and streaming data pipelines using Kafka, Airflow, or Spark Familiarity with governance frameworks, access controls (RBAC), and implementation of pseudonymisation and retention policies Exposure to enabling GenAI and ML workloads by preparing model-ready and vector-optimised datasets More ❯

with excellent collaboration skills. Grit in the face of technical obstacles. Nice to have: Building SDKs or client libraries to support API consumption. Knowledge of distributed data processing frameworks (Spark, Dask). Understanding of GPU orchestration and optimization in Kubernetes. Familiarity with MLOps and ML model lifecycle pipelines. Experience with AI model training and fine-tuning. Familiarity with event More ❯

source systems into our reporting solutions. Pipeline Development: Develop and configure meta-data driven data pipelines using data orchestration tools such as Azure Data factory and engineering tools like Apache Spark to ensure seamless data flow. Monitoring and Failure Recovery: Implement monitoring procedures to detect failures or unusual data profiles and establish recovery processes to maintain data integrity. … in Azure data tooling such as Synapse Analytics, Microsoft Fabric, Azure Data Lake Storage/One Lake, and Azure Data Factory. Understanding of data extraction from vendor REST APIs. Spark/Pyspark or Python skills a bonus or a willingness to develop these skills. Experience with monitoring and failure recovery in data pipelines. Excellent problem-solving skills and attention More ❯

best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and ETL/ELT development in More ❯

cloud technologies and modern engineering practices. ● Experience with the following technologies: o Cloud Provider: AWS o Languages: Python, PHP, Rust & SQL o Hosting: Kubernetes o Tooling & Analytics: Airflow, RabbitMQ, Apache Spark, PowerBI ● Proven ability to complete projects according to outlined scope, budget, and timeline ● Experience with industry standard tools such as Microsoft products, Jira, confluence, project management tools More ❯

cloud technologies and modern engineering practices. ● Experience with the following technologies: o Cloud Provider: AWS o Languages: Python, PHP, Rust & SQL o Hosting: Kubernetes o Tooling & Analytics: Airflow, RabbitMQ, Apache Spark, PowerBI ● Proven ability to complete projects according to outlined scope, budget, and timeline ● Experience with industry standard tools such as Microsoft products, Jira, confluence, project management tools More ❯

data infrastructure or data platforms, with proven ability to solve complex distributed systems challenges independently Expertise in large-scale data processing pipelines (batch and streaming) using technologies such as Spark, Kafka, Flink, or Beam Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform More ❯

data infrastructure or data platforms, with proven ability to solve complex distributed systems challenges independently Expertise in large-scale data processing pipelines (batch and streaming) using technologies such as Spark, Kafka, Flink, or Beam Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform More ❯

data infrastructure or data platforms, with proven ability to solve complex distributed systems challenges independently Expertise in large-scale data processing pipelines (batch and streaming) using technologies such as Spark, Kafka, Flink, or Beam Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform More ❯

data infrastructure or data platforms, with proven ability to solve complex distributed systems challenges independently Expertise in large-scale data processing pipelines (batch and streaming) using technologies such as Spark, Kafka, Flink, or Beam Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform More ❯

data infrastructure or data platforms, with proven ability to solve complex distributed systems challenges independently Expertise in large-scale data processing pipelines (batch and streaming) using technologies such as Spark, Kafka, Flink, or Beam Experience designing and implementing large-scale data storage systems (feature stores, timeseries databases, warehouses, or object stores) Strong distributed systems and infrastructure skills (Kubernetes, Terraform More ❯

practices for data infrastructure, fostering a culture of collaboration and knowledge sharing. (Required) Kubernetes and Orchestration: Manage and optimize Kubernetes clusters, specifically for running critical data processing workloads using Spark and Airflow. (Required) Cloud Security: Implement and maintain robust security measures, including cloud networking, IAM, encryption, data isolation, and secure service communication (VPC peering, PrivateLink, PSC/PSA). More ❯

version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. are a plus. Additional Information What’s More ❯

Java, TypeScript, Python, and Go Web libraries and frameworks such as React and Angular Designing, building, and maintaining CI/CD pipelines Big data technologies, such as NiFi, Hadoop, Spark Cloud and containerization technologies such as AWS, OpenShift, Kubernetes, Docker DevOps methodologies, such as infrastructure as code and GitOps Database technologies, e.g. relational databases, Elasticsearch, Mongo Why join Gemba More ❯