1 to 25 of 125 Permanent Apache Spark Jobs in England

Profisee), Snowflake Data Integration, Azure Service Bus, Deltalake, BigQuery, Azure DevOps, Azure Monitor, Azure Data Factory, SQL Server, Azure DataLake Storage, Azure App Service, Apache Airflow, Apache Iceberg, Apache Spark, Apache Hudi, Apache Kafka, Power BI, BigQuery, Azure ML is a plus Experience with … Azure SQL Database, Cosmos DB, NoSQL, MongoDB Experience with Agile, DevOps methodologies Awareness and knowledge of ELT/ETL, DWH, APIs (RESTful), Spark APIs, FTP protocols, SSL, SFTP, PKI (Public Key Infrastructure) and Integration testing Skills and Abilities Knowledge of Python, SQL, SSIS, and Spark languages. Demonstrative ability 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 »

Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure SQL Database, Azure Stream Analytics, etc. Strong Python or Scala with Spark, PySpark experience Experience with relational databases and NoSQL databases Significant experience and in-depth knowledge of creating data pipelines and associated design principles, standards … Ability to design and implement data warehousing solutions using Azure Synapse Analytics. Azure Databricks: Proficiency in using Azure Databricks for data processing and analytics. Apache Spark: Deep understanding of Apache Spark for large-scale data processing. Azure Blob Storage and Azure Data Lake Storage: Expertise in more »

Certified Solutions Architect, AWS Certified Data Analytics Specialty, or AWS Certified Big Data Specialty. Experience with other big data and streaming technologies such as Apache Spark, Apache Flink, or Apache Beam. Knowledge of containerization and orchestration technologies such as Docker and Kubernetes. Experience with data lakes 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 »

workplace where each employee's privacy and personal dignity is respected and protected from offensive or threatening behaviour including violence and sexual harassment Role: Apache Spark Application Developer Skills Required: Hands on Experience as a software engineer in a globally distributed team working with Scala, Java programming language … preferably both) Experience with big-data technologies Spark/Databricks and Hadoop/ADLS is a must Experience in any one of the cloud platform Azure (Preferred), AWS or Google Experience building data lakes and data pipelines in cloud using Azure and Databricks or similar tools. Spark Developer more »

data engineering or a similar role. > Proficiency in programming languages such as Python, Java, or Scala. > Strong experience with data processing frameworks such as Apache Spark, Apache Flink, or Hadoop. > Hands-on experience with cloud platforms such as AWS, Google Cloud, or Azure. > Experience with data warehousing more »

working closely with our product teams on existing projects and new innovations to support company growth and profitability. Our Tech Stack Python Scala Kotlin Spark Google PubSub Elasticsearch, Bigquery, PostgresQL Kubernetes, Docker, Airflow Key Responsibilities Designing and implementing scalable data pipelines using tools such as Apache Spark … Data Infrastructure projects, as well as designing and building data intensive applications and services. Experience with data processing and distributed computing frameworks such as Apache Spark Expert knowledge in one or more of the following languages - Python, Scala, Java, Kotlin Deep knowledge of data modelling, data access, and more »

data pipelines using tools such as Airflow, Jenkins and GitHub actions. · Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala · Help the business harness the power of data within easyJet, supporting them with insight, analytics and data … system. · Significant experience with Python, and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). · Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Arrow, MapR). · Significant experience with SQL – comfortable writing efficient SQL. · Experience using … enterprise scheduling tools (e.g. Apache Airflow, Spring DataFlow, Control-M) · Experience with Linux and containerisation What you’ll get in return ·Competitive base salary ·Up to 20% bonus ·25 days holiday ·BAYE, SAYE & Performance share schemes ·7% pension ·Life Insurance ·Work Away Scheme ·Flexible benefits package ·Excellent staff travel 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 »

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 »

development (ideally AWS) and container technologies Strong communication and interpersonal skills Experience managing projects and working with external third party teams Ideally experience with Apache Spark or Apache Flink (but not essential) Please note, this role is unable to provide sponsorship. If this role sounds of interest more »

IaC), automation & configuration management; Ansible (plus Puppet, Saltstack), Terraform, CloudFormation; NodeJS, REACT/MaterialUI (plus Angular), Python, JavaScript; Big data processing and analysis, e.g. Apache Hadoop (CDH), Apache Spark; RedHat Enterprise Linux, CentOS, Debian or Ubuntu. Java 8, Spring framework (preferably Spring boot), AMQP RabbitMQ, Open source 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 »

s preferred). Excellent problem-solving and communication. Can be advantageous if you have: Cloud platform experience (AWS, Azure, GCP), big data tech (Hadoop, Spark), containerization (Docker, Kubernetes), DevOps and CI/CD understanding. We regret to inform you that only shortlisted candidates will be notified/contacted. 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 »

team has strong appetite to embrace latest tech stacks offered in the industry. We need passionate software engineers who use Java, JavaScript, Python, React, Apache Spark and open source data science toolkits to build solutions that offer best in class experience to our risk managers and analysts. Our … solving and analytical skills Preferred Qualifications Strong programming experience in at least one language Comfortable with working with multiple languages Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) Experience with continuous delivery and deployment Proficient at working with large 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 »

field (STEM) Technical proficiency in cloud-based data solutions (AWS, Azure or GCP), engineering languages including Python, SQL, Java, and pipeline management tools e.g., Apache Airflow. Familiarity with big data technologies, Hadoop, or Spark. If this opportunity is of interest, or you know anyone who would be interested in more »

run on AWS and soon Azure, with plans to also add GCP and on-prem. They are adding extensive usage of distributed compute on Spark, starting with their more complex ETL and advanced analytics functions, e.g. Time Series Processing. They soon plan to integrate other approaches, including native distributed … PyTorch/Tensorflow, Spark-based distributor libraries, or Horovod. TECH STACK: Python, Flask, Redis, Postgres, React, Plotly, Docker. Temporal; AWS Athena SQL, Athena & EMR Spark, ECS Fargate; Azure Synapse/Data Lake Analytics, HDInsight. KEY RESPONSIBILITIES Lead the productionisation of Monolith’s ML models and data processing pipelines … both mid-low-level system and design and exemplary hands-on implementations using Spark and other tech stacks Shape the ML engineering culture and practices around model & data versioning, scalability, model benchmarking, ML-specific branching & release strategy Concisely break down complex high-level ML requirements into smaller deliverables (epic 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 »

and able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to more »

and able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to more »

requires candidates to go through SC Clearance, so you must be eligible. Experience of AWS tools (e.g Athena, Redshift, Glue, EMR) Java, Scala, Python, Spark, SQL Experience of developing enterprise grade ETL/ELT data pipelines. NoSQL Databases. Dynamo DB/Neo4j/Elastic, Google Cloud Datastore. Snowflake Data more »