13 of 13 Apache Spark Jobs in the East of England

design, implement, and optimize enterprise-scale data platforms using the Databricks Lakehouse Platform . The ideal candidate will have deep expertise in Databricks architecture, Apache Spark, Delta Lake, data engineering, cloud platforms, and enterprise data solutions. Key Responsibilities Design and architect Databricks Lakehouse solutions for large-scaleenterprise data … Databricks implementation, including architecture, development, deployment, and optimization. Define Databricks workspace architecture, clusterstrategies, security models, and operational standards. Design and developscalable data pipelinesusing Databricks, Apache Spark, PySpark, SQL, andDelta Lake . Implement data ingestionframeworks supporting batchand real-timedata processing. Design Delta Lake architectures including: Delta tables Medallion architecture ...

control (Git) and related software lifecycle tooling.Experience with tooling for monitoring, logging and alerting e.g. Splunk, New Relic or Grafana.Experience of technologies such as Apache Spark, Databricks, Snowflake, or BigQuery to transform big-data optimised for Tesco scaleExperience building solutions that run in the cloud, ideally Azure.Experience with … control (Git) and related software lifecycle tooling.Experience with tooling for monitoring, logging and alerting e.g. Splunk, New Relic or Grafana.Experience of technologies such as Apache Spark, Databricks, Snowflake, or BigQuery to transform big-data optimised for Tesco scaleExperience building solutions that run in the cloud, ideally Azure.Experience with ...

Analytics, Artificial Intelligence or a related field, or equivalent experience, would be effective, although practical experience is equally valuable.“Nice to Have”Azure, Databricks, Apache Spark or comparable cloud and data platforms.Data pipelines, ETL and workflow-orchestration technologies.Machine-learning methods such as forecasting, prediction or classification.Experience with enterprise ...

degree, or experience in a professional field or military Experience as technical specialist in design and architecture Experience in database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) Experience in consulting, design and implementation of serverless distributed solutions Experience in software development with object oriented language Experience in cloud based ...

tools e.g. Microsoft Power BI, Spotfire, TableauExperience of briefing and communication analytical products to non-technical staffExperience of using big data ecosystems e.g. Hadoop, Spark and/or MapReduce.Experience of working in NATO or similar multi-national defence/security sector. Why work with us By joining our organization ...

devise strategic solutions, and lead their implementation.Good written and verbal communication skills.Any Beneficial/Nice to have experience: Experience with Big Data technology (HDFS, Spark, Impala)Understanding of Cloud-native development principles.Experience with Container Orchestration tools (Docker, Kubernetes, OpenShift, etc.).Proficiency in using Jira for tracking tasks, managing backlogs ...

with modern NLP stack and multi-modal representation learning is a plusWe’d love to see that you’ve worked with big data systems (Spark, S3, and Airflow) and can program (Java, Scala, or Python)Good understanding of system architecture. Have experience in big data technologies and streaming architecture ...

leadership teams. Minimum Qualifications Masters in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science or equivalent Proficiency in data querying using SQL, Spark, or equivalent technologies Proficiency in scripting languages for data processing and analysis (ex: Python, R, or Scala) Excellent communication and multi-functional collaboration skills ...

scripting language — Python is required.Proficiency in at least one object-oriented language.Experience with big data technologies such as HDFS, YARN, MapReduce, Hive, Kafka, Spark, Airflow, or Presto.Experience with AWS, GCP, or Looker (advantageous but not essential).Solid background in data modelling, including the design, implementation and optimisation of conceptual ...

Python is required . Proficiency in at least one object-oriented language. Experience with big data technologies such as HDFS, YARN, MapReduce, Hive, Kafka, Spark, Airflow, or Presto. Experience with AWS, GCP, or Looker (advantageous but not essential). Solid background in data modelling, including the design, implementation ...

spans a wide range of technologies, including Java and Python-based MicroServices, AWS/GCP cloud backend systems, Big Data technologies like Hive and Spark, and modern Web applications. With a globally distributed presence across the US, India and Europe, the team thrives on collaboration, bringing together diverse perspectives … needs, entrepreneurial spiritExcellent verbal and written communication skillsBS or MS degree in Computer Science or equivalentExperience in distributed computing frameworks like - Hive/Hadoop, Apache SparkExperience in developing Finance or HR related applicationsExperience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, LambdaWorking ...

across devices and platforms to surface key metrics. The role emphasizes coding in Python, strong SQL, and experience with large data ecosystems (HDFS, Hive, Spark, Airflow). You will influence architecture and own initiatives from concept to delivery. Hybrid work from Cambridge Office. #J-18808-Ljbffr ...

engineering role spanning modelling, large-scale training, and production infrastructure — you’ll take models from idea through to serving at scale, working in Spark, Python, and Java. You’ll work closely with Praveen and the wider Ad Performance ML team. Based in the UK (Manchester-anchored).How will … ship ML models for ad relevance and bid/yield optimizationBuild and maintain production ML infrastructure for real-time, low-latency servingWork across Spark, Python, and Java to move models from research to productionApply sound feature engineering, validation, and evaluation practices throughout the modelling lifecycleDiagnose production ML issues such ...