1 to 25 of 156 Permanent Apache Spark Jobs in the UK

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 »

Senior Scala Developer - Apache Spark - Urgent Requirement Contract Length: 6 Months IR35 status: Inside Location: London - Hybrid working A Senior Scala Developer with experience in Apache Spark is needed for a British consultancy organisation. You will be an integral member of the team providing technical expertise … you will be able to implement ETL pipelines to process, transform, and standardize data from various sources as well as optimise the performance of Spark applications. Work closely with data scientists, software engineers, and machine learning experts to enhance the data platform and contribute to the development of cloud more »

Lead Data Engineer (Director) - Individual contributor - Azure, Data Factory, Databricks, Apache Spark - London Based I am hiring for a Lead Data Engineer for a crucial role within one of my Investment Bank clients in London. This role is at Director level as they require a very senior candidate … Leading data engineering practices Support current applications Introduce AI practices to the team/project Communicate key successes with stakeholders Key Skills: Azure Databricks Apache Spark Datascience, AI, ML Certifications or continued upskilling/contribution to blog posts within Data & AI beneficial but not essential. This is a … without sponsorship, if you are interested please apply or email me directly - aaron.dhammi@nicollcurtin.com Lead Data Engineer (Director) - Individual contributor - Azure, Data Factory, Databricks, Apache Spark - London Based more »

Data Scientists and Service Engineering teams Experience with design, development and operations that leverages deep knowledge in the use of services like Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon EMR, NoSQL technologies and other 3rd parties Develop and define key business questions and to build … a related field Experience of Data platform implementation, including 3+ years of hands-on experience in implementation and performance tuning Kinesis/Kafka/Spark/Storm implementations Experience with analytic solutions applied to the Marketing or Risk needs of enterprises Basic understanding of machine learning fundamentals Ability to … take Machine Learning models and implement them as part of data pipeline IT platform implementation experience Experience with one or more relevant tools ( Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis) Experience developing software code in one or more programming languages (Java, JavaScript, Python, etc) Current hands-on implementation experience more »

Spark Architect/SME Contract Role- 6 months to begin with & its extendable Location: Leeds, UK (min 3 days onsite) Context: Legacy ETL code for example DataStage is being refactored into PySpark using Prophecy low-code no-code and available converters. Converted code is causing failures/performance issues. … Skills: Spark Architecture – component understanding around Spark Data Integration (PySpark, scripting, variable setting etc.), Spark SQL, Spark Explain plans. Spark SME – Be able to analyse Spark code failures through Spark Plans and make correcting recommendations. Spark SME – Be able to review PySpark … and Spark SQL jobs and make performance improvement recommendations. Spark – SME Be able to understand Data Frames/Resilient Distributed Data Sets and understand any memory related problems and make corrective recommendations. Monitoring – Be able to monitor Spark jobs using wider tools such as Grafana to see more »

prem solutions to the cloud, including re-architecting Prior experience working on data focused projects e.g. data warehousing, big data, data streaming Proficiency with Apache Kafka, Apache Spark, Apache Flink etc. We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless 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 Ke y 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 components such as Azure Data Factory, Azure SQL DB, Azure Data Lake, etc. Strong Python and SQL skills for data manipulation Experience with Apache Spark and/or Databricks. Familiarity with BI visualization tools like Power BI Experience in managing end-to-end analytics pipelines (batch and … such as Azure Data Engineer Associate are desirable. Knowledge of data ingestion methods for real-time and batch processing Proficiency in PySpark and debugging Apache Spark workloads. What’s in it for you? Annual bonus scheme – up to 10% Excellent pension scheme Flexible working Enhanced family friendly policies more »

delivering moderate-to-complex data flows as part of a development team in collaboration with others. You’ll be confident using technologies such as: Apache Kafka, Apache NiFi, SAS DI Studio, or other data integration platforms. You can implement, deliver, and translate several data models, including unstructured data … and recognised standards to build solutions using various traditional or big data languages such as: SQL, PL/SQL, SAS Macro Language, Python, Scala, Apache Spark, Java, JavaScript etc, using various tools including SAS, Hue (Hive/Impala), Kibana (Elastic Search). Knowledge of data management on Cloud more »

preferably in a senior or lead role Strong proficiency in programming languages Python Expertise in designing and building data pipelines using ETL tools like Apache Spark or Apache Beam Experience with cloud-based data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake Proficiency in SQL more »

development (ideally AWS) Knowledge and ideally hands-on experience with data streaming, event-based architectures and Kafka Strong communication and interpersonal skills Experience with Apache Spark or Apache Flink would be ideal, but not essential Please note, this role is unable to provide sponsorship. If this role more »

Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands more »

at scale utilising the best breed of Cloud services and technologies. So, what tools and technologies will you be using? AWS Python Databricks/Spark Trino Airflow Docker CloudFormation/Terraform SQL/NoSQL We provide you with the opportunity to think freely and work creatively and right now … Other skills we are looking for you to demonstrate include: Experience of data storage technologies: Delta Lake, Iceberg, Hudi Sound knowledge and understanding of Apache Spark, Databricks or Hadoop Ability to take business requirements and translate these into tech specifications Knowledge of Architecture best practices and patterns Competence more »

AWS Redshift, and Python Experience with ETL processes, data integration, and data warehousing. Strong SQL skills Experience with Big Data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud platforms (AWS, Azure, Google Cloud) Working knowledge of data visualisation tools (PowerBI, Tableau, Qlik Sense) Additional skills: Client-facing 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 »

DataBricks, Azure SQL (Indicative experience = 5yrs+) Build and test processes supporting data extraction, data transformation, data structures, metadata, dependency and workload management. Knowledge on Spark architecture and modern Datawarehouse/Data-Lake/Lakehouse techniques Build transformation tables using SQL. Moderate level knowledge of Python/PySpark or equivalent more »

pipelines Know your way around Unix based operating system Experience working with any major cloud provider (AWS, GCP, Azure) Fluency in English Experience using Apache Airflow Experience using Docker Experience using Apache Spark Benefits: Salary £40-50K per annum dependant on skills and experience 25 Days 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 »

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 »

AWS Redshift, and Python Experience with ETL processes, data integration, and data warehousing. Strong SQL skills Experience with Big Data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud platforms (AWS, Azure, Google Cloud) Working knowledge of data visualisation tools (PowerBI, Tableau, Qlik Sense) Additional Skills: Client-facing more »

Google Cloud Professional Cloud Architect or Professional Cloud Developer certification Very Disrable to have hands-on experience with ETL tools, Hadoop-based technologies (e.g., Spark), and batch/streaming data pipelines (e.g., Beam, Flink etc) Proven expertise in designing and constructing data lakes and data warehouse solutions utilising technologies more »

Google Cloud Professional Cloud Architect or Professional Cloud Developer certification Very Disrable to have hands-on experience with ETL tools, Hadoop-based technologies (e.g., Spark), and batch/streaming data pipelines (e.g., Beam, Flink etc) Proven expertise in designing and constructing data lakes and data warehouse solutions utilising technologies more »

data engineering technology stack compatible with AWS. Experience with web scraping and other data ingestion methods and tools. Knowledge of distributed computing frameworks (Hadoop, Spark, Hive, Presto). Experience with data orchestration tools (Airflow, Orchestra, Azkaban). Expertise in cloud data warehousing and core data modelling concepts. Proficiency in more »