1 to 25 of 133 Apache Spark Jobs in England

Responsibilities: As a pivotal member of our rapidly expanding business, your role involves: Designing and Maintaining Data Architectures and Pipelines: Create and optimize robust data architectures and pipelines. Assemble intricate data sets that align with both functional and non-functional more »

Experience with a JVM language, Kotlin, Java, Scala, Clojure Knowledge of Typescript and React is beneficial Exposure to data pipelines using technologies such as Spark and Kafka Experience with cloud services (ideally AWS) Hybrid working 1-2 days per week in Central London. £110,000 depending on experience. Please more »

Experience with a JVM language, Kotlin, Java, Scala, Clojure Knowledge of Typescript and React is beneficial Exposure to data pipelines using technologies such as Spark and Kafka Experience with cloud services (ideally AWS) Hybrid working 1-2 days per week in Central London. £110,000 depending on experience. Please more »

working with AWS technologies such as Lambda, ECS Fargate, API Gateway, RDS, DynamoDB, EMR building customer-facing applications and APIs building data pipelines using Spark + Scala that process Tb of data per day working with customers to understand the business context of new features participating in design reviews more »

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 »

What you’ll be using: 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. If this sounds like you, be sure to get in touch – we are shortlisting right away. If you like the sound of the opportunity, but don’t quite tick every box more »

comfortable designing and constructing bespoke solutions and components from scratch to solve the hardest problems. Adept in Java, Scala, and big data technologies like Apache Kafka and Apache Spark, they bring a deep understanding of engineering best practices. This role involves scoping and sizing, and indeed estimating … be considered. Key responsibilities of the role are summarised below Design and implement large-scale data processing systems using distributed computing frameworks such as Apache Kafka and Apache Spark. Architect cloud-based solutions capable of handling petabytes of data. Lead the automation of CI/CD pipelines for more »

Skills: Strong knowledge of SQL and experience with data analysis tools such as Excel, Tableau, and PowerBI. Experience with data processing technologies such as Apache Spark and Apache Flink. Knowledge of statistical analysis techniques and experience with programming languages such as Python, R, and SAS. Strong problem 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 »

/data stores (object storage, document or key-value stores, graph databases, column-family databases) • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR, Snowflake, and Data Mesh principles • Team player • Proactive and resilient • A passion for social good Our Mission Statement: We are an equal opportunity more »

VBA as well as batch scripting (e.g. PowerShell) • experience of Python (including TM1Py), Apliqo UX (Cubewise) and Azure Kubernetes is beneficial • broader experience of Apache Spark (Databricks), Business Intelligence (Power BI) and Machine Learning also beneficial • strong analytical, problem-solving and synthesizing skills (you know how to figure more »

skills include: Experience deploying, securing and supporting cloud infrastructure platforms Understanding of security frameworks/standards Understanding of data streaming and messaging frameworks (Kafka, Spark, etc.) and modern database technologies (Cockroach etc.) Understanding of distributed tracing and monitoring (Zipkin, OpenTracing, Prometheus, ELK stack, Micrometer metrics, etc.) Experience with containers 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 »

SQL Data Warehouse, Azure Data Lake, Azure Databricks Azure Cosmos DB, Azure Data Factory, Azure Search, Azure Stream Analytics Delta Lake and Data Lakes Apache Spark Pools, SQL Pools (dpools and spools) Experience in Python, C# coding, Spark, PySpark, Unix shell/Perl scripting experience Experience in more »

Python, R, or Java. Solid understanding of data manipulation, modeling, and analysis techniques. Familiarity with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark) is a plus. Experience with cloud platforms and services (e.g., AWS, Azure, GCP) for machine learning model deployment and management is advantageous. Excellent problem more »

to: Backend technology, Python. Databases like MSSQL. Front-end technology, Java. Cloud platform, AWS. Programming language, JavaScript (React.js) Big data technologies such as Hadoop, Spark, or Kafka. What We Need from You: Essential Skills: A degree in Computer Science, Engineering, or a related field, or equivalent experience. Proficiency in more »

pipeline and workflow management and their tools such as Airflow. Strong understanding of relational SQL and NoSQL databases, including MongoDB and stream-processing systems: Spark-Streaming, Kinesis etc. Ability to understand any scripting language and tools. Rewards & Benefits TCS is consistently voted a Top Employer in the UK and more »

cross-functionally across the business to understand the requirements of the products Designing and implementing performance related data ingestion pipelines from multiple sources using Apache Spark Integrating end-to-end data pipelines ensuring a high level of quality is maintained Working with an Agile delivery/DevOps methodology more »

complex issues they are facing. out data-driven analysis, craft solutions to resolve business problems. Artificial Intelligence and data science approaches (Python, R, Matlab, Spark etc). database technologies such as Hadoop. tools that expand the companies tool kit, advancing their ability to serve clients. Experience needed- in a more »

the cloud, ideally including the use of scalable technologies such as cluster computing and containerization Experience working in parallel/scalable languages such as Spark or Dask Experience working with knowledge graphs and graph neural networks Biotech or biopharma experience, ideally within R&D Experience in a startup or more »

capital while also giving them the flexibility to decide when and how they use it. LIQUiDITY is backed by top global financial institutions, including Spark Capital, MUFG, Apollo, and Meitav Dash. We are looking for Credit Directors who are ready to build the next generation of machine-learning-powered more »

of scalable backend services using Go, Rust, and other relevant technologies. Spearhead the adoption of cutting-edge technologies like Kubernetes, Knative, Rook, Cassandra, and Spark to enhance our product offerings and infrastructure. Set the technical direction for the team, ensuring alignment with the company’s strategic goals and industry more »

an easy and developer friendly platform to create, manage and monitor their own kafka infrastructure Help drive our stream processing platform, whether it be Apache Flink, Spark, or another relevant technology Collaborate with cross-functional teams to design, develop, and implement scalable and reliable solutions Troubleshoot and resolve more »

PACKAGED GOODS (RCG) Extensive experience working with large data sets with hands-on technology skills to design and build robust Big Data solutions using Spark PySpark framework and Industry standard frameworks like Databricks Azure DevOps and other tools technologies on Azure Cloud Platform Key Roles and Responsibilities: Understand the … business development and ensuring high levels of client satisfaction during deliver Skills Must have strong hands-on technical Skills in Python Pyspark Azure Databricks Spark ETL Cloud Azure preferred Good to have knowledge on ADF CI CD more »

you'll spearhead backend and data engineering and mentor team members. Tech stack: Athena; Python, Flask, Redis, Postgres, React, Plotly, Docker, SQL, Athena & EMR Spark, ECS and Temporal. This is a 50/50 split between tech and leadership. Your background: 8 years+ coding experience, 4+ years need to … cloud infrastructure (AWS, Azure, GCP) Start-up experience is preferred but not essential. The extras: Experience working on AI-based products. Distributed computing experience (Spark, MPI, etc) Experience orchestrating workflows, particularly within distributed system environments. Knowledge of MLOps principles and practices, especially in implementing them within production settings. What more »