1 to 25 of 314 Apache Spark Jobs in the UK excluding London

data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB. The data engineer is proficient in Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB. They are also proficient in Azure Event Hub and Streaming Analytics, Managed Streaming for Apache Kafka, Azure … DataBricks with Spark, and other open source technologies like Apache Airflow and dbt, Spark/Python, or Spark/Scala. Preferred Education Bachelor's Degree Required Technical And Professional Expertise Commercial experience as a Data Engineer or similar role, with a strong emphasis on Azure technologies. Proficiency in Azure data services (Azure SQL Database, Azure Synapse … Analytics, Azure Data Factory, Azure Databricks). Experience with data modeling, data warehousing, and big data processing (Hadoop, Spark, Kafka). Strong understanding of SQL and NoSQL databases, data modeling, and ETL/ELT processes. Proficiency in at least one programming language (Python, C#, Java). Experience with CI/CD pipelines and tools (Azure DevOps, Jenkins). Knowledge More ❯

In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform. You will leverage your expertise in PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability. If you have a passion for data engineering and … significant impact, we encourage you to apply! Job Responsibilities ETL/ELT Pipeline Development: Design, develop, and optimize efficient and scalable ETL/ELT pipelines using Python, PySpark, and Apache Airflow. Implement batch and real-time data processing solutions using Apache Spark. Ensure data quality, governance, and security throughout the data lifecycle. Cloud Data Engineering: Manage and optimize … effectiveness. Implement and maintain CI/CD pipelines for data workflows to ensure smooth and reliable deployments. Big Data & Analytics: Develop and optimize large-scale data processing pipelines using Apache Spark and PySpark. Implement data partitioning, caching, and performance tuning techniques to enhance Spark-based workloads. Work with diverse data formats (structured and unstructured) to support advanced More ❯

SQL Cloud platform architecture (AWS, Azure, GCP) Data Warehousing (Snowflake, Redshift, Synapse, BigQuery, etc.) Data Lakes/Lakehouses and analytical tools (Databricks, Azure Fabric/OneLake, AWS Lake Formation, Spark, Athena, etc.) Relational, NoSQL, graph and vector databases Streaming technologies (Kafka, Kinesis, Flink, etc.) Containers and related services (Docker, Kubernetes, container Registries, etc) CI/CD and other DevOps … practices such as IaC Testing Nice to have - Additional experience with the following would be beneficial but not essential: Data modelling approaches (Kimball, Imnon) Orchestration tools - Apache Airflow, Prefect or cloud-native tools Backend software development (Java, APIs, Scalability, Logging and Monitoring etc.) MLFlow and other MLOps/Machine Learning Engineering processes to support advanced analytical use cases LLMs More ❯

In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform. You will leverage your expertise in PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability. If you have a passion for data engineering and … to apply! Job Responsibilities Data Engineering & Data Pipeline Development Design, develop, and optimize scalable DATA workflows using Python, PySpark, and Airflow Implement real-time and batch data processing using Spark Enforce best practices for data quality, governance, and security throughout the data lifecycle Ensure data availability, reliability and performance through monitoring and automation. Cloud Data Engineering : Manage cloud infrastructure … data processing workloads Implement CI/CD pipelines for data workflows to ensure smooth and reliable deployments. Big Data & Analytics: Build and optimize large-scale data processing pipelines using Apache Spark and PySpark Implement data partitioning, caching, and performance tuning for Spark-based workloads. Work with diverse data formats (structured and unstructured) to support advanced analytics and More ❯

In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform. You will leverage your expertise in PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability. If you have a passion for data engineering and … to apply! Job Responsibilities Data Engineering & Data Pipeline Development Design, develop, and optimize scalable DATA workflows using Python, PySpark, and Airflow Implement real-time and batch data processing using Spark Enforce best practices for data quality, governance, and security throughout the data lifecycle Ensure data availability, reliability and performance through monitoring and automation. Cloud Data Engineering : Manage cloud infrastructure … data processing workloads Implement CI/CD pipelines for data workflows to ensure smooth and reliable deployments. Big Data & Analytics: Build and optimize large-scale data processing pipelines using Apache Spark and PySpark Implement data partitioning, caching, and performance tuning for Spark-based workloads. Work with diverse data formats (structured and unstructured) to support advanced analytics and More ❯

Knowledge And Expertise Hands-on experience in building ELT pipelines and working with large-scale datasets using Azure Data Factory (ADF) and Databricks. Strong proficiency in SQL (T-SQL, Spark SQL) for data extraction, transformation, and optimisation. Proficiency in Azure Databricks (PySpark, Delta Lake, Spark SQL) for big data processing. Knowledge of data warehousing concepts and relational database … Lake for schema evolution, ACID transactions, and time travel in Databricks. Strong Python (PySpark) skills for big data processing and automation. Experience with Scala (optional but preferred for advanced Spark applications). Experience working with Databricks Workflows & Jobs for data orchestration. Strong knowledge of feature engineering and feature stores, particularly in Databricks Feature store for ML training and inference. … Experience with data modelling techniques to support analytics and reporting. Familiarity with real-time data processing and API integrations (e.g., Kafka, Spark Streaming). Proficiency in CI/CD pipelines for data deployment using Azure DevOps, GitHub Actions, or Terraform for Infrastructure as Code (IaC). Understanding of MLOps principles, including continuous integration (CI), continuous delivery (CD), and continuous More ❯

Site Reliability Engineer or 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, with experience in automation and scripting. More ❯

Data Engineer (Informatica/Teradata/Datawarehouse) page is loaded Data Engineer (Informatica/Teradata/Datawarehouse) Apply locations Two PNC Plaza (PA374) Birmingham - Brock (AL112) Dallas Innovation Center - Luna Rd (TX270) Strongsville Technology Center (OH537) time type Full time More ❯

production issues. Optimize applications for performance and responsiveness. Stay Up to Date with Technology: Keep yourself and the team updated on the latest Python technologies, frameworks, and tools like Apache Spark , Databricks , Apache Pulsar , Apache Airflow , Temporal , and Apache Flink , sharing knowledge and suggesting improvements. Documentation: Contribute to clear and concise documentation for software, processes … cloud platforms like AWS , GCP , or Azure . DevOps Tools: Familiarity with containerization ( Docker ) and infrastructure automation tools like Terraform or Ansible . Real-time Data Streaming: Experience with Apache Pulsar or similar systems for real-time messaging and stream processing is a plus. Data Engineering: Experience with Apache Spark , Databricks , or similar big data platforms for … processing large datasets, building data pipelines, and machine learning workflows. Workflow Orchestration: Familiarity with tools like Apache Airflow or Temporal for managing workflows and scheduling jobs in distributed systems. Stream Processing: Experience with Apache Flink or other stream processing frameworks is a plus. Desired Skills: Asynchronous Programming: Familiarity with asynchronous programming tools like Celery or asyncio . Frontend More ❯

maintain the data platform. You will be working on complex data problems in a challenging and fun environment, using some of the latest Big Data open-source technologies like Apache Spark, as well as Amazon Web Service technologies including Elastic MapReduce, Athena and Lambda to develop scalable data solutions. Key Responsibilities: Adhering to Company Policies and Procedures with … and specifications. Good interpersonal skills, positive attitude, willing to help other members of the team. Experience debugging and dealing with failures on business-critical systems. Preferred Qualifications: Exposure to Apache Spark, Apache Trino, or another big data processing system. Knowledge of streaming data principles and best practices. Understanding of database technologies and standards. Experience working on large More ❯

Job Accountabilities Develop robust, scalable data pipelines to serve the easyJet analyst and data science community. Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala. Work with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploy machine learning models and algorithms aimed at … indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data … e.g. access management, data privacy, handling of sensitive data (e.g. GDPR) Desirable Skills Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. Understanding of the challenges faced in the design and development of a streaming data pipeline and the different options for processing unbounded data (pubsub More ❯

exciting and critical challenges to the UK's 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 with … the option of compressed hours. The role will include: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data ingestion, transformation, and integration processes, ensuring data quality and security. Collaborate with data architects and security teams to ensure compliance with security policies and data governance standards. Manage and … experience working as a Data Engineer in secure or regulated environments. Expertise in the Elastic Stack (Elasticsearch, Logstash, Kibana) for data ingestion, transformation, indexing, and visualization. Strong experience with Apache NiFi for building and managing complex data flows and integration processes. Knowledge of security practices for handling sensitive data, including encryption, anonymization, and access control. Familiarity with data governance More ❯

exciting and critical challenges to the UK’s 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 with … the option of compressed hours. The role will include: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data ingestion, transformation, and integration processes, ensuring data quality and security. Collaborate with data architects and security teams to ensure compliance with security policies and data governance standards. Manage and … experience working as a Data Engineer in secure or regulated environments. Expertise in the Elastic Stack (Elasticsearch, Logstash, Kibana) for data ingestion, transformation, indexing, and visualization. Strong experience with Apache NiFi for building and managing complex data flows and integration processes. Knowledge of security practices for handling sensitive data, including encryption, anonymization, and access control. Familiarity with data governance More ❯

Azure, or Google Cloud Platform (GCP) Strong proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or Oracle Experience with big data technologies such as Hadoop, Spark, or Hive Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow Proficiency in Python and at least one other programming language More ❯

of experience in data engineering or a related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT pipelines . Proficiency More ❯

quality of our tools and applications through bug fixes and code refactoring. Leverage the latest data technologies and programming languages, including Python, Scala, and Java, along with systems like Spark, Kafka, and Airflow, within cloud services such as AWS. Ensure the ongoing maintenance, troubleshooting, optimization, and reliability of data systems, including timely resolution of unexpected issues. Stay abreast of … Strong knowledge of relational and NoSQL databases (e.g., PostgreSQL, MongoDB) and data modeling principles. Proven ability to design, build, and maintain scalable data pipelines and workflows using tools like Apache Airflow or similar. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Nice to have: Hands-on experience with data warehouse and lakehouse architectures (e.g., Databricks, Snowflake … or similar). Experience with big data frameworks (e.g., Apache Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, or GCP). #J-18808-Ljbffr More ❯

technical and professional experience Preferred Skills: Experience working within the public sector. Knowledge of cloud platforms (e.g., IBM Cloud, AWS, Azure). Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop). Understanding of data warehousing concepts and experience with tools like IBM Cognos or Tableau. Certifications:While not required, the following certifications would be highly beneficial … Experience working within the public sector. Knowledge of cloud platforms (e.g., IBM Cloud, AWS, Azure). Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop). Understanding of data warehousing concepts and experience with tools like IBM Cognos or Tableau. ABOUT BUSINESS UNIT IBM Consulting is IBM's consulting and global professional services business, with market leading More ❯

years of experience in data engineering or a related field, with a focus on building scalable data systems and platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency in SQL and More ❯

related issues Strong analytical and problem-solving skills Strong teamwork, interpersonal and collaboration skills with colleagues and clients Desirable: Experience with Cloud ETL tools such as Databricks/Snowflake, Spark and Kafka Experience using source control tools such as GitHub or Azure DevOps Experience with Azure DevOps for CI/CD pipeline development and data operations (DataOps) Experience with More ❯

SageMaker, GCP AI Platform, Azure ML, or equivalent). • Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). • Leadership & Communication: • Proven ability to lead cross-functional teams in ambiguous startup settings. • Exceptional written and verbal communication skills—able to explain complex concepts to both technical More ❯

We are seeking 3 Data Engineers to join our defence & security client on a contract basis. Key skills required for this role DV cleared, Data Engineer, ETL, Elastic Stack, Apache NiFi Important DV Cleared - Data Engineer - ELK & NiFi - Outside IR35 Location: Worcester Duration: 6 months initial contract Security: Active DV clearance required In this role, you will help design … develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. These positions are onsite in Worcester and require active UK DV clearance. Key Responsibilities: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack and Apache NiFi. Implement data ingestion, transformation, and integration processes, ensuring data quality … the ability to obtain it. Experience as a Data Engineer in secure or regulated environments. Expertise in the Elastic Stack for data ingestion, transformation, and visualization. Strong experience with Apache NiFi for managing complex data flows. Knowledge of security practices for handling sensitive data. Understanding of data governance, quality, and compliance standards in secure settings. Experience managing large-scale More ❯

field. Technical Skills Required Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). Experience with Apache Spark or any other distributed data programming frameworks. Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. Experience with cloud infrastructure like AWS … Skills Hands-on development experience in an airline, e-commerce or retail industry Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. Experience implementing end-to-end monitoring, quality checks, lineage tracking and automated alerts to ensure reliable and trustworthy data across the platform. Experience of More ❯

the UK for the last 10 years, and ability to obtain security clearance. Preferred Skills Experience with cloud platforms (IBM Cloud, AWS, Azure). Knowledge of big data frameworks (Apache Spark, Hadoop). Experience with data warehousing tools like IBM Cognos or Tableau. Certifications in relevant technologies are a plus. Additional Details Seniority level: Mid-Senior level Employment More ❯

working with relational and non-relational databases to build data solutions, such as SQL Server/Oracle , experience with relational and dimensional data structures. Experience in using distributed frameworks ( Spark, Flink, Beam, Hadoop ). Proficiency in infrastructure as code (IaC) using Terraform . Experience with CI/CD pipelines and related tools/frameworks. Containerisation: Good knowledge of containers … AWS, or Azure . Good understanding of cloud storage, networking, and resource provisioning. It would be great if you had... Certification in GCP “Professional Data Engineer”. Certification in Apache Kafka (CCDAK). Proficiency across the data lifecycle. Working for us: Our focus is to ensure we are inclusive every day, building an organisation that reflects modern society and More ❯

for data models, ETL processes, and BI solutions. Ensure data accuracy, integrity, and consistency across the data platform. Knowledge, Skills and Experience: Essentia l Strong expertise in Databricks and Apache Spark for data engineering and analytics. Proficient in SQL and Python/PySpark for data transformation and analysis. Experience in data lakehouse development and Delta Lake optimisation. Experience More ❯