1 to 25 of 53 Apache Spark Jobs in England with Remote Work Options

and practical troubleshooting skills. Tools Platforms & Tools : Cloud Computing platforms (ADLS Gen2), Microsoft Stack (Synapse, DataBricks, Fabric, Profisee), Snowflake Data Integration, Azure Service Bus, Apache Airflow, Apache Iceberg, Apache Spark, Apache Hudi, Apache Kafka, Power BI, BigQuery, DeltaLake, Azure DevOps, Azure Monitor, Azure Data … Server, Azure DataLake Storage, Azure App Service, Azure ML is a plus. Languages : Python, SQL, T-SQL, SSIS, and high-level programming knowledge on Spark is a plus. DB: Azure SQL Database, Cosmos DB, NoSQL, MongoDB, and HBase are a plus Methodologies: Agile and DevOps must have Concepts: ELT …/ETL, DWH, APIs (RESTful), Spark APIs, FTP protocols, SSL, SFTP, PKI (Public Key Infrastructure) and Integration testing more »

CD, and model monitoring. Proficiency in Python and relevant data manipulation and analysis libraries (e.g., pandas, NumPy). Experience with distributed computing frameworks like Apache Spark is a plus. Apache Spark and Airflow would be a bonus. Role overview: If you're looking to work with more »

CD, and model monitoring. Proficiency in Python and relevant data manipulation and analysis libraries (e.g., pandas, NumPy). Experience with distributed computing frameworks like Apache Spark is a plus. Apache Spark and Airflow would be a bonus. Role overview: If you're looking to work with more »

of the company's data infrastructure. You will work with some of the most innovative tools in the market including Snowflake, AWS (Glue, S3), Apache Spark, Apache Airflow and DBT!! The role is hybrid, with 2 days in the office in central London and the company is more »

the UK). Role Overview: In this vital role, you will develop and maintain enterprise-grade software systems leveraging your expertise in Databricks, Python, Spark, R, and SQL. You will collaborate closely with our architecture team to design scalable, clean solutions that support continuous delivery and improvement. Your contributions more »

automation. The Role As a Data Engineer with us, you will: Design, develop and maintain scalable and efficient data pipelines and ETL processes using Spark, ensuring high-quality data processing and integration. Collaborate with cross-functional teams to translate complex data requirements into actionable technical solutions. Utilize Microsoft Azure … highest standards in database design and operations. The Person We're looking for someone who is: Experienced as a Data Engineer, demonstrating proficiency in Apache Spark and cloud-based technologies, especially Microsoft Azure and Databricks. Skilled in programming, particularly Python, and familiar with data integration tools and ETL more »

and product development, encompassing experience in both stream and batch processing. · Designing and deploying production data pipelines, utilizing languages such as Java, Python, Scala, Spark, and SQL. In addition, you should have proficiency or familiarity with: · Scripting and data extraction via APIs, along with composing SQL queries. · Integrating data more »

Terraform/Docker/Kubernetes. Write software using either Java/Scala/Python . The following are nice to have, but not required - Apache Spark jobs and pipelines. Experience with any functional programming language. Database design concepts. Writing and analysing SQL queries. Application overVIOOH Our recruitment team more »

emphasis on Pyspark and Databricks for this particular role. Technical Skills Required: Azure (ADF, Functions, Blob Storage, Data Lake Storage, Azure Data Bricks) Databricks Spark Delta Lake SQL Python PySpark ADLS Day To Day Responsibilities: Extensive experience in designing, developing, and managing end-to-end data pipelines, ETL (Extract more »

in programming languages and tools for data analysis, such as Python, R, and SQL You must be proficient in big data technologies, such as Spark, Kafka and/or Hadoop. A strong understanding of statistical analysis, predictive modelling, machine learning algorithms, and data development and optimisation is essential You more »

with data ingestion tools such as Airbyte and Fivetran, accommodating a wide array of data sources. Mastery of large-scale data processing techniques using Spark or Dask. Strong programming skills in Python, Scala, C#, or Java, and adeptness with cloud SDKs and APIs. Deep understanding of AI/ML more »

for seamless data integration. * Understanding of DevOps best practices for SQL and Power BI projects, including DACPAC, CI/CD, and versioning. * Familiarity with Apache Spark for big data processing. * Additional development experience in Python or related technologies. * Experience gained within a Media, Travel or Broadcast Media sectors more »

pivotal role in designing, building, and maintaining their data infrastructure while collaborating closely with senior stakeholders across the organisation. Your expertise in Azure, Databricks, Spark, Python, and data modelling will be critical in driving the success of their data initiatives. Key Responsibilities: Lead the complete development cycle of data … comprehensive of data modelling, data warehousing principles, and the innovative Lakehouse architecture. Exceptional proficiency in ETL methodologies, preferably utilising Azure Databricks or equivalent technologies (Spark, Spark SQL, Python, SQL), including deep insight into ETL/ELT design patterns. Proficient in Databricks, SQL, and Python, with a robust understanding more »

for enhanced performance and scalability. Requirements: Professional Experience: At least four years of relevant data engineering experience. Technical Proficiency: Strong familiarity with Azure Databricks, Spark, Hive, Python, and SQL. Knowledge of Azure cloud services such as Data Factory and Storage accounts is highly regarded. Data System Mastery: Proven ability more »

in at least two of the following technologies/programming languages: Java, .Net, C#, ETL tools (e.g. Informatica, Azure Data Framework, Databricks), Maven, spring, Spark (Scala/Python), SQL (e.g. PostgreSQL) and noSQL database design/implementation • strong experience in providing and integrating API’s in a service-oriented more »

Essential Skills Proven experience as a Data Engineer Well versed in the following: cloud-based data storage solutions, data lakes, customer data platforms. (Python, Spark, SQL, Cloud Data Environments such as AWS, GCP, Azure) Good understanding of data modelling methods and data partitioning and compaction methods in Data Lake more »

etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark etc) Experience with Cloud platforms (AWS, GCP or Azure) This is a fully remote role, but may require very occasional travel (once a month more »

APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. Senior ML Learning Engineer desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud AWS, Google Cloud, Azure, and a knowledge of secure coding techniques PCI-DSS, PA-DSS, ISO27001. This is a fantastic opportunity to join more »

tools such as Informatica MDM, Informatica AXON, Informatica EDC, and Collibra • MySQL, SQL Server, Oracle, Snowflake, PostgreSQL and NoSQL databases • Programming languages such as Spark or Python • Amazon Web Services, Microsoft Azure or Google Cloud and distributed processing technologies such as Hadoop Benefits : • Base Salary more »

Linux, APIs, infrastructure design – load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer – desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud – AWS, Google Cloud, Azure, and a knowledge of secure coding techniques – PCI-DSS, PA-DSS, ISO27001. Note: as there are actually two roles more »

Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud AWS, Google Cloud, Azure, and a knowledge of secure coding techniques PCI-DSS, PA-DSS, ISO27001. Note: as there are actually two roles more »

Linux, APIs, infrastructure design – load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer – desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud – AWS, Google Cloud, Azure, and a knowledge of secure coding techniques – PCI-DSS, PA-DSS, ISO27001. Note: as there are actually two roles more »

mining, data analysis, and strong software engineering skills. Strong understanding of Data Engineering Proficiency in AWS, data warehousing (Snowflake, Databricks, Redshift), big data frameworks (Spark, Kafka), container orchestration platforms (Kubernetes), and data integration/ETL tools. Strong written and verbal communication skills, with the ability to explain technical concepts more »

execute Understand the nuances of dealing with structured and unstructured data, and be experienced in using databases (Mongo ideally) Experience with Linux Experience with Spark (Pyspark), Hadoop or other Big data technologies would be beneficial, but not required Benefits Why we think you'll enjoy it here: Base Salary more »

solutions Proficiency in data pipeline orchestration across hybrid environments, leveraging the latest in Azure and allied technologies. Expertise in data processing with tools like Spark or Dask, and fluency in Python, Scala, C#, or Java. Expertise in DevOps and CI/CD automation , ensuring seamless deployment with tools like more »