1 to 25 of 34 Permanent Flink Jobs in the UK

diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies: Utilize big data technologies such as Spark, Kafka, and Flink for distributed data processing and analytics. Cloud Platforms: Deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging cloud-native services More ❯

diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies: Utilize big data technologies such as Spark, Kafka, and Flink for distributed data processing and analytics. Cloud Platforms: Deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging cloud-native services More ❯

table/file formats: Delta Lake, Parquet, Iceberg, Hudi Previous h ands-on expertise with Spark Experience working with containerisation technologies - Docker, Kubernetes Streaming Knowledge: Experience with Kafka/Flink or other streaming ecosystems, with a solid understanding of their components DevOps experience building CI/CD pipelines (Jenkins), IaC (Terraform) Direct experience contributing to projects involving lakehouse/ More ❯

Comfortable using Git; an awareness of CI/CD practices and tools such as GitHub Actions or Azure DevOps Nice to have: Experience of working with Apache Spark/Flink/Kafka Familiarity with object storage e.g. AWS S3 Knowledge of containerised development workflows using e.g., VSCode Basic understanding of cloud platforms like AWS or GCP Experience contributing to More ❯

CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage frameworks like Great Expectations More ❯

Advanced skills in Python or another major language; writing clean, testable, production-grade ETL code at scale. Modern Data Pipelines: Experience with batch and streaming frameworks (e.g., Apache Spark, Flink, Kafka Streams, Beam), including orchestration via Airflow, Prefect or Dagster. Data Modeling & Schema Management: Demonstrated expertise in designing, evolving, and documenting schemas (OLAP/OLTP, dimensional, star/snowflake More ❯

Advanced skills in Python or another major language; writing clean, testable, production-grade ETL code at scale. Modern Data Pipelines: Experience with batch and streaming frameworks (e.g., Apache Spark, Flink, Kafka Streams, Beam), including orchestration via Airflow, Prefect or Dagster. Data Modeling & Schema Management: Demonstrated expertise in designing, evolving, and documenting schemas (OLAP/OLTP, dimensional, star/snowflake More ❯

Experience working in environments with AI/ML components or interest in learning data workflows for ML applications . Bonus if you have e xposure to Kafka, Spark, or Flink . Experience with data compliance regulations (GDPR). What you can expect from us: Salary 65-75k Opportunity for annual bonuses Medical Insurance Cycle to work scheme Work More ❯

are recognised by industry leaders like Gartner's Magic Quadrant, Forrester Wave and Frost Radar. Our tech stack: Superset and similar data visualisation tools. ETL tools: Airflow, DBT, Airbyte, Flink, etc. Data warehousing and storage solutions: ClickHouse, Trino, S3. AWS Cloud, Kubernetes, Helm. Relevant programming languages for data engineering tasks: SQL, Python, Java, etc. What you will be doing More ❯

solutions in an Agile environment. Technical Proficiency: Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (Kafka, Flink, DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. CI/CD: Detailed understanding More ❯

solutions in an Agile environment. Technical Proficiency: Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (Kafka, Flink, DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. CI/CD: Detailed understanding More ❯

in a high-ownership, fast-paced environment. Nice to have: Experience working in the Payments, Fintech, or Financial Crime domain (e.g., fraud detection, AML, KYC). Experience with Apache Flink or other streaming data frameworks is highly desirable. Experience working in teams, building and maintaining data science and AI solutions. Experience integrating with third-party APIs, especially in regulated More ❯

Hands-on experience with SQL, Data Pipelines, Data Orchestration and Integration Tools Experience in data platforms on premises/cloud using technologies such as: Hadoop, Kafka, Apache Spark, Apache Flink, object, relational and NoSQL data stores. Hands-on experience with big data application development and cloud data warehousing (e.g. Hadoop, Spark, Redshift, Snowflake, GCP BigQuery) Expertise in building data More ❯

or Extract, Load, Transform (ELT) workflows to move data from source systems to date stores.* Experience with one or more of the following supporting technologies: Apache, Kafka, NiFi, Spark, Flink or Airflow etc.* Past experience working with SQL and NoSQL databases (e.g. PostgreSQL, Mongo, Elasticsearch, Accumulo or Neo4j).* Hands-on experience with distributed computing, ETL, data pipelines, and More ❯

expertise in: The python data engineering stack (Polars, Parquet, FastAPI, Jupyter, Airflow, Streamlit, Ray) High-performance data stores and query engines (Starburst, Snowflake) Real-time streaming analytics technologies (Kafka, Flink) Cloud container technologies (AWS, Azure, GCP, Docker, Kubernetes) Proven success in enhancing developer experience that reduces friction in coding, building and deploying APIs and client libraries. Real-world application More ❯

with big data technologies ( e.g. , Spark, Hadoop)Background in time-series analysis and forecastingExperience with data governance and security best practicesReal-time data streaming is a plus (Kafka, Beam, Flink)Experience with Kubernetes is a plusEnergy/maritime domain knowledge is a plus What We Offer Competitive salary commensurate with experience and comprehensive benefits package (medical, dental, vision) Significant More ❯

with a focus on data quality and reliability. Design and manage data storage solutions, including databases, warehouses, and lakes. Leverage cloud-native services and distributed processing tools (e.g., Apache Flink, AWS Batch) to support large-scale data workloads. Operations & Tooling Monitor, troubleshoot, and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and security … pipelines and data architectures. Hands-on expertise with cloud platforms (e.g., AWS) and cloud-native data services. Comfortable with big data tools and distributed processing frameworks such as Apache Flink or AWS Batch. Strong understanding of data governance, security, and best practices for data quality. Effective communicator with the ability to work across technical and non-technical teams. Additional … following prior to applying to GSR? Experience level, applicable to this role? Select How many years have you designed, built, and operated stateful, exactly once streaming pipelines in Apache Flink (or an equivalent framework such as Spark Structured Streaming or Kafka Streams)? Select Which statement best describes your hands on responsibility for architecting and tuning cloud native data lake More ❯

join a fast-growing team that plays an integral part of the revenue producing arm of a company, then our team is for you. Technologies include Scala, Python, Apache Flink, Spark, Databricks, and AWS (ECS, Lambda, DynamoDB, WAF, among others). Experience in these areas is preferred but not required. Qualifications: You collaborate with team members and project management More ❯

stack technologies including; Java, JavaScript, TypeScript, React, APIs, MongoDB, Elastic Search, DMN, BPMN and Kubernetes leverage data-streaming technologies including Kafka CDC, Kafka topic and related technologies, EMS, Apache Flink be able to innovate and incubate new ideas, have an opportunity to work on a broad range of problems, often dealing with large data sets, including real-time processing More ❯

and constructive feedback to foster accountability, growth, and collaboration within the team. Who You Are Experienced with Data Processing Frameworks: Skilled with higher-level JVM-based frameworks such as Flink, Beam, Dataflow, or Spark. Comfortable with Ambiguity: Able to work through loosely defined problems and thrive in autonomous team environments. Skilled in Cloud-based Environments: Proficient with large-scale More ❯

data or backend engineering, while growing the ability to work effectively across both. Experience with processing large-scale transactional and financial data, using batch/streaming frameworks like Spark, Flink, or Beam (with Scala for data engineering), and building scalable backend systems in Java. You possess a foundational understanding of system design, data structures, and algorithms, coupled with a More ❯

Familiarity with geospatial data formats (e.g., GeoJSON, Shapefiles, KML) and tools (e.g., PostGIS, GDAL, GeoServer). Technical Skills: Expertise in big data frameworks and technologies (e.g., Hadoop, Spark, Kafka, Flink) for processing large datasets. Proficiency in programming languages such as Python, Java, or Scala, with a focus on big data frameworks and APIs. Experience with cloud services and technologies … related field. Experience with data visualization tools and libraries (e.g., Tableau, D3.js, Mapbox, Leaflet) for displaying geospatial insights and analytics. Familiarity with real-time stream processing frameworks (e.g., Apache Flink, Kafka Streams). Experience with geospatial data processing libraries (e.g., GDAL, Shapely, Fiona). Background in defense, national security, or environmental monitoring applications is a plus. Compensation and Benefits More ❯

us achieve our objectives. So each team leverages the technology that fits their needs best. You'll see us working with data processing/streaming like Kinesis, Spark and Flink; application technologies like PostgreSQL, Redis & DynamoDB; and breaking things using in-house chaos principles and tools such as Gatling to drive load all deployed and hosted on AWS. Our More ❯

plus Experience with Terraform and Kubernetes is a plus! A genuine excitement for significantly scaling large data systems Technologies we use (experience not required): AWS serverless architectures Kubernetes Spark Flink Databricks Parquet. Iceberg, Delta lake, Paimon Terraform Github including Github Actions Java PostgreSQL About Chainalysis Blockchain technology is powering a growing wave of innovation. Businesses and governments around the More ❯

Craft: Data, Analytics & Strategy Job Description: Activision Blizzard Media is the gateway for brands to the cross-platform gaming company in the western world, with hundreds of millions of players across over 190 countries. Our legendary portfolio includes iconic mobile More ❯