13 of 13 Remote/Hybrid Flink Jobs in London

managing real-time data pipelines across a track record of multiple initiatives. Expertise in developing data backbones using distributed streaming platforms (Kafka, Spark Streaming, Flink, etc.). Experience working with cloud platforms such as AWS, GCP, or Azure for real-time data ingestion and storage. Programming skills in Python ...

cloud strategy — contributing to cloud adoption initiatives, deploying Citi APIs on AWS and Azure Working with event streaming and messaging systems including Kafka, Flink, and Solace at enterprise scale This is a rare opportunity in financial services — a stable, well‐funded platform with the freedom to keep building ...

modelling: designing schemas and storage for relational databases, warehouses or lakehouses, and understanding when each fits. Distributed processing: working with systems such as Spark, Flink or Beam, including how partitioning, parallelism, skew, memory, failures and ordering affect results. Platform experience Cloud and infrastructure as code: building infrastructure with tools ...

consumer or marketplace environment. Deep understanding of distributed systems and modern data ecosystems — including extensive experience with Databricks, Apache Spark, Apache Kafka, Apache Flink, Apache Beam and DBT. Demonstrated success in designing, building, and operating data platforms at scale, encompassing both batch processing and real-time streaming architectures. Expertise ...

Spring components, including Spring Data JPA. Experience with containerisation technologies such as Docker and Kubernetes. Experience with stream processing frameworks such as Apache Flink is a plus but not required. Familiarity with SSO mechanisms including OpenID is a plus but not required. A basic understanding of core microservice components ...

where people feel safe to challenge ideas, learn, and grow. Nice to have Hands-on familiarity with the modern data stack — for example, Spark, Flink, Kafka, Debezium, Airflow, dbt, or similar — and with cloud platforms (AWS/GCP or equivalent) and modern DevOps practices. Experience leading teams that built ...

production-grade code Distributed Data Processing Experience building and operating: batch processing systems distributed data systems near real-time streaming pipelines Familiarity with: Kafka Flink Spark Databricks experience is a strong plus Databases & Data Warehousing Comfortable working with: RDBMS data warehousing solutions Strong understanding of data modelling aligned with ...

meetups Continuously learn and improve engineering practices What we’re looking for batch processing distributed data processing Experience with technologies such as: Kafka Flink Spark Databricks experience is a plus Experience implementing: Data Lakes Big Data Analytics platforms Cloud-based solutions experience AWS preferred Software Engineering Expertise with: RDBMS ...

rather than relying on frameworks such as Spring. You have built event‐driven applications using Kafka and solutions with event‐streaming frameworks at scale (Flink/Kafka Streams/Spark) that go beyond basic ETL pipelines. You know how to orchestrate the deployment of applications on Kubernetes, including defining ...

comfortable working with large-scale datasets using SQL and platforms such as BigQuery. You have experience with JVM-based data processing frameworks such as Flink, Beam, Dataflow, or Spark. You are familiar with DevOps practices, cloud infrastructure, containerized applications, and Kubernetes fundamentals. You have experience with data modeling ...

more across different environments Technologies We Use Different backend languages, including Java, Rust, and Go Open-source technologies like Cassandra, ElasticSearch, Spark, Kafka, Kubernetes, Flink Industry-standard build tooling, including Gradle and GitHub What We Value Demonstrated ability to collaborate and empathise with a variety of individuals. Able ...

applying algorithms within a commercial environment Prior experience working with highly imbalanced datasets for binary classification problems Event streaming data engineering tools such as Flink or Spark Experience with MLOps and tools such as Airflow, BentoML and MLFlow Use of Docker CI/CD and SDLC (e.g. JIRA ...

technology/infrastructure which will serve hundreds of teams and petabyte-level volumes of data. Key Responsibilities Work with stream processing technologies (Kafka and Flink) to build a continuously available large-scale event streaming platform Leverage subject matter and technical expertise to provide leadership, mentoring, and strategic influence across … implementing and owning event streaming platforms Hands-on experience working with stream technologies, ideally Kafka Experience designing and implementing stream processing applications with Flink Experience working with cloud-based technologies such as AWS (MSK, S3, Lambda, ECS, SNS) Experience with Kubernetes (either self-hosted or on the cloud) Experience ...