101 to 125 of 164 Apache Spark Jobs in the UK

Pharmaceutical industry experience Experience in distributed system design Experience with Pure/Alloy Working knowledge of open-source tools such as AWS lambda, Prometheus Spark, Hadoop orSnowflake knowledge would be a plus. Additional Information Location: This role can be delivered in a hybrid nature from one of these offices more »

Pharmaceutical industry experience Experience in distributed system design Experience with Pure/Alloy Working knowledge of open-source tools such as AWS lambda, Prometheus Spark, Hadoop orSnowflake knowledge would be a plus. Additional Information Location: This role can be delivered in a hybrid nature from one of these offices more »

designing and building robust, scalable, distributed data systems and pipelines, using open source and public cloud technologies. Strong experience with data orchestration tools: e.g. Apache Airflow, Dagster. Experience with big data storage and processing technologies: e.g. DBT, Spark, SQL, Athena/Trino, Redshift, Snowflake, RDBMSs (PostgreSQL/MySQL … . Knowledge of event-driven architectures and streaming technologies: e.g. Apache Kafka, Kafka Streams, Apache Flink. Experience with public cloud environments: e.g. AWS, GCP, Azure, Terraform. Strong knowledge of software engineering practices: e.g. testing, CI/CD (Jenkins, Github Actions), agile development, git/version control, containers etc. more »

Hybrid-3 days a week JOB DETAILS Must Have - Platform engineer, Azure DevOps and CI/CD tools, Azure Cloud, Microsoft Fabric, Azure Services, Apache Spark, Experience of using IAC (terraform, APIs), Data Engineer, Big Data, PySpark more »

master and meta data management Experience with Azure SQL Database, Azure Data Factory, Azure Storage, Azure IaaS/PaaS related database implementations. Experience with Apache spark and new Fabric framework would be a plus. more »

for business improvements Lead a small team of data scientist on Neural Networks LLMs (CNN & RNN), ML, & NLP NLP/AI/ML/Spark/Python/Data scientist/Machine Learning Engineer/OCR/Deep Learning Requirements Bachelor's degree or equivalent experience in quantitative field more »

Service, tackling the ML Ops loop as a service, interesting challenge. They are going to enable edge AI, another pioneering aspect. Tech stack: Athena, Spark, ECS, Temporal, Python, Flask, Redis, Postgres, React, Plotly, Docker 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 Strong consulting 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 »

MongoDB/DynamoDB/etc.) Solid understanding of data governance principles and how to implement these across the business Knowledge of Big Data technology (Spark/Hadoop/etc.) Excellent communication skills across various levels of stakeholders Benefits: Salary available £120,000 Bonus scheme Enhanced pension contribution available Genuine more »

of databases. Snowflake is widely used, as are Docker and Kubernetes for containerisation. ETL and ELT tech are also used every day, primarily Airflow, Spark, Hive and a lot more. You’ll need to come from a strong academic background with some commercial experience in a data heavy software more »

reports. 7. Knowledge of data integration techniques and tools (e.g., SSIS, Informatica) is desirable. 8. Experience in working with big data technologies (e.g., Hadoop, Spark) is a plus. 9. Excellent communication and collaboration skills, with the ability to effectively interact with technical and non-technical stakeholders. 10. Strong attention more »

and manage data lake/data warehouse platforms. (Some of the following types of providers: AWS, Microsoft Azure, Google Cloud Platform, Databricks, Snowflake, Cloudera, Spark, MongoDB) Done this at companies using high volumes of data, ideally in retailing. Other sectors where used high volume data would also be relevant more »

Redshift, DynamoDB, Glue and SageMaker Infrastructure-as-Code tools and approaches (we use the AWS CDK with CloudFormation) Data processing frameworks such as pandas, Spark and PySpark Machine learning concepts like model training, model registry, model deployment and monitoring Development and CI/CD tools (we use GitHub, CodePipeline more »

DW/BI systems · Demonstrated ability in data modeling, ETL development, and Data warehousing. · Strong experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.) · Expertise in a BI solution like Power BI · Hands on experience in modelling databases (particularly nosql), working on indexes, materialized views, performance tuning … with impressive visualization (Power BI) · Experience in building large scale DW/BI systems for B2B SAAS companies · Experience with open-source tools like Apache Flink and AWS tools like S3, Redshift, EMR and RDS. · Experience with AI/Machine Learning and Predictive Analytics · Experience in developing global products more »

processes, and data warehousing. - Significant exposure and hands on at least 2 of the programming languages - Python, Java, Scala, GoLang. - Significant experience with Hadoop, Spark and other distributed processing platforms and frameworks. - Experience working with Open table/storage formats like delta lake, apache iceberg or apache hudi. - Experience of developing and managing real time data streaming pipelines using Change data capture (CDC), Kafka and Apache Spark. - Experience with SQL and database management systems such as Oracle, MySQL or PostgreSQL. - Strong understanding of data governance, data quality, data contracts, and data security best practices. - Exposure more »

we encourage you to apply. Python App Developer Requirements: Proficiency with Python or PySpark. Exposure to cloud technologies such as Airflow, Astronomer, Kubernetes, AWS, Spark, Kafka. Experience with Big Data solutions or Relational DB. Demonstrated knowledge of software applications and technical processes within a cloud or microservice architecture. Hands more »

DevOps experience in CI/CD. Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow. Experience using Python is a must (tools like AWS and Spark are beneficial) Excellent communication skills and team and colleague engagement. A keen interest in problem-solving and using scalable machine learning to solve the more »

DevOps experience in CI/CD. Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow. Experience using Python is a must (tools like AWS and Spark are beneficial) Excellent communication skills and team and colleague engagement. A keen interest in problem-solving and using scalable machine learning to solve the more »

and implement pre-processing pipelines for large data, create visualisation and reports for model performance, whilst collaborating with various engineers to improve knowledge and spark innovation. As the Machine Learning Engineer you will ideally have a degree in a relevant industry; Computer Science, Maths, AI, or similar, at least more »

DevOps experience in CI/CD. Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow. Experience using Python is a must (tools like AWS and Spark are beneficial) Excellent communication skills and team and colleague engagement. A keen interest in problem-solving and using scalable machine learning to solve the more »

in Python, R, and SQL. Extensive experience (over 5 years) in building Machine Learning models. Understanding of underlying data systems like Cloud architectures, K8S, Spark, and SQL. Fluency in English and German, with French being a plus. Desirable experience in Consulting or Customer-facing Data Science roles, Data Engineering more »

you! Minimum Qualifications Bachelors or Masters Degree in Engineering or Computer Applications Hands-on experience with MS SQL Server and GCP Familiarity with BQ, Spark, Hive, Pig, and other analytical tools. Understanding of finance domain. Preferred Qualification Experience in SAP data modelling Genpact is an Equal Opportunity Employer and more »

wrangling, modelling, feature engineering and deployment What's equally relevant is programming knowledge and a gift for coding using: R, Python, SQL, SAS or Spark You'll also need the capability to deliver projects, collaborate with operational teams and be able to explain technical concepts to non-specialists What more »

engineer will supply advice to analytical users on how they can access and utilise the new datasets. Qualities Comfortable with Python - ideally experience with Apache Spark and Pyspark Previous data analytics software experience Able to scope new integrations and translate analytical user needs into technical requirement. UK based more »