1 to 25 of 51 Remote Apache Spark Jobs in the UK excluding London

focused data team responsible for building and optimising scalable, production-grade data pipelines and infrastructure. Key Responsibilities: Design and implement robust, scalable ETL/ELT pipelines using Databricks and Apache Spark Ingest, transform, and manage large volumes of data from diverse sources Collaborate with analysts, data scientists, and business stakeholders to deliver clean, accessible datasets Ensure high performance … practices Work with cloud-native tools and services (preferably Azure ) Required Skills & Experience: Proven experience as a Data Engineer on cloud-based projects Strong hands-on skills with Databricks , Apache Spark , and Python or Scala Proficient in SQL and working with large-scale data environments Experience with Delta Lake , Azure Data Lake , or similar technologies Familiarity with version More ❯

lead Support the Ordnance Survey Testing Community, with common standards such as metrics and use of test tools Here is a snapshot of the technologies that we use Scala, Apache Spark, Databricks, Apache Parquet, YAML, Azure Cloud Platform, Azure DevOps (Test plans, Backlogs, Pipelines), GIT, GeoJSON What we're looking for Highly skilled in creating, maintaining and 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 ❯

tools (Git, Maven, Jenkins, CI/CD) Excellent communication and teamwork skills Bonus Points For Experience in payments, financial services, or fraud detection Familiarity with Big Data tools (Hadoop, Spark, Kafka) Exposure to cloud-native architecture (AWS, GCP, Azure) Understanding of TDD/BDD and modern testing frameworks What's On Offer Hybrid Working - Flexibility with 2 remote days More ❯

systems Clear communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools More ❯

systems Clear communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools More ❯

Driven Projects: Collaborate on exciting and complex data pipelines, platforms, and automation solutions across industries including finance, retail, and government. Cutting-Edge Tech: Work hands-on with tools like Spark, Databricks, Azure Deequ, and more. Career Development: We invest in your growth with dedicated training, mentoring, and support for certifications. Collaborative Culture: Join a diverse, inclusive team that thrives … you'll do: Maintain test automation frameworks tailored for data-intensive environments. Implement validation tests for data pipelines, data quality, and data transformation logic. Use tools like Azure Deequ , Spark , and Databricks to ensure data accuracy and completeness. Write robust, scalable test scripts in Scala , Python , and Java . Integrate testing into CI/CD pipelines and support infrastructure … and data validation techniques. Experience using test automation frameworks for data pipelines and ETL workflows Strong communication and stakeholder management skills. Nice-to-Have: Hands-on experience with Databricks , Apache Spark , and Azure Deequ . Familiarity with Big Data tools and distributed data processing. Experience with data observability and data quality monitoring. Proficiency with CI/CD tools More ❯

Catalog). Familiarity with Data Mesh, Data Fabric, and product-led data strategies. Expertise in cloud platforms (AWS, Azure, GCP, Snowflake). Technical Skills Proficiency in big data tools (Apache Spark, Hadoop). Programming knowledge (Python, R, Java) is a plus. Understanding of ETL/ELT, SQL, NoSQL, and data visualisation tools. Awareness of ML/AI integration More ❯

knowledge of Kafka , Confluent , and event-driven architecture Hands-on experience with Databricks , Unity Catalog , and Lakehouse architectures Strong architectural understanding across AWS, Azure, GCP , and Snowflake Familiarity with Apache Spark, SQL/NoSQL databases, and programming (Python, R, Java) Knowledge of data visualisation, DevOps principles, and ML/AI integration into data architectures Strong grasp of data More ❯

Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments Managing cloud infrastructure with a DevOps approach Handling and transforming various data types (JSON, CSV, etc.) using Apache Spark, Databricks, or Hadoop Understanding modern data system architectures (Data Warehouse, Data Lakes, Data Meshes) and their use cases Creating data pipelines on cloud platforms with error handling More ❯

Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments Managing cloud infrastructure with a DevOps approach Handling and transforming various data types (JSON, CSV, etc.) using Apache Spark, Databricks, or Hadoop Understanding modern data system architectures (Data Warehouse, Data Lakes, Data Meshes) and their use cases Creating data pipelines on cloud platforms with error handling More ❯

Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments Managing cloud infrastructure with a DevOps approach Handling and transforming various data types (JSON, CSV, etc.) using Apache Spark, Databricks, or Hadoop Understanding modern data system architectures (Data Warehouse, Data Lakes, Data Meshes) and their use cases Creating data pipelines on cloud platforms with error handling More ❯

their growth and development Apply agile methodologies (Scrum, pair programming, etc.) to deliver value iteratively Essential Skills & Experience Extensive hands-on experience with programming languages such as Python, Scala, Spark, and SQL Strong background in building and maintaining data pipelines and infrastructure In-depth knowledge of cloud platforms and native cloud services (e.g., AWS, Azure, or GCP) Familiarity with More ❯

moreprogramming languages such asPython, R, and SQL. An understanding of databasetheory and design. Experience withSQL and NoSQL databases. Familiarity with big datatechnologies and ecosystems suchas MicrosoftSynapse/Fabric,Hadoop, Spark, Kafka, and others. Skills in data modelling and datawarehousing solutions. Experienceof dimensional modelling (Kimball). Proven Experience in designing and developing ETL/ELT processes. Knowledge of data pipeline More ❯

Agile projects Skills & Experience: Proven experience as a Lead Data Solution Architect in consulting environments Expertise in cloud platforms (AWS, Azure, GCP, Snowflake) Strong knowledge of big data technologies (Spark, Hadoop), ETL/ELT, and data modelling Familiarity with Python, R, Java, SQL, NoSQL, and data visualisation tools Understanding of machine learning and AI integration in data architecture Experience 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 ❯

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 ❯

and running hybrids. Container orchestration deployment, configuration, and administration. (e.g. Docker Swarm, Kubernetes). Automation and configuration management (e.g., Ansible, Puppet, Chef). Analytics infrastructure and tooling (e.g. Databricks, Apache Spark). Technical leadership, championing standard methodologies, and leading technical product transformations. In Return: We are proud to have a set of behaviours that reflect our culture and More ❯

to support data needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL More ❯

to support data needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL More ❯

to support data needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL More ❯

orchestrators!) Data platform expertise, knowledge of lakehouse architectures, Delta Lake, or real-time data processing patterns. Experience working in hybrid environments with asynchronous teamwork. Tuning, profiling and optimising Kafka, Spark, or container networking under load. In Return: This role is at the heart of a highly leveraged platform, enabling hundreds of engineers to use critical data systems with confidence. More ❯

control providers, preferably Git Proven to be an excellent communicator with a clear passion for data & analytics. Deep engineering and database skills in SQL, Server Azure Synapse, Data factory, spark compute and Databricks technologies. Experience of developing coding standards and deliver methods that others follow. Experience of testing techniques, tools and approaches. Extensive experience of the full data lifecycle. More ❯