1 to 25 of 45 Flink Jobs in London

Python and/or other modern programming languages. Experience developing and orchestrating data pipelines using technologies such as DBT, Apache Spark, Airflow, Dagster, Kafka, Flink, or equivalent tooling. Solid understanding of data lakehouse, warehouse, and medallion architecture patterns. Experience applying DevOps and DataOps best practices including CI/ ...

Hands-on experience building, scaling, and shipping large-scale data platforms in production. Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop). Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis). End-to-end exposure to data pipeline lifecycle ...

Proven experience designing and building scalable data pipelines (ETL/ELT) for batch and streaming use cases using modern technologies (e.g., Python, SQL, Spark, Flink, Airflow) and advanced knowledge on the workings of these. Hands-on experience in building and operating workloads Databricks. Hands-on experience creating data visualizations ...

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 ...

columnar formats, or analytics engines (e.g., ClickHouse, TimescaleDB, Druid, InfluxDB, Parquet). Experience with streaming or data processing technologies such as Kafka, Apache Arrow, Flink, or Spark. Comfort reasoning about distributed systems tradeoffs: latency vs. throughput, consistency vs. availability, abstraction vs. control. Clear technical communication and a bias toward ...

development. Proficiency in SQL and programming languages such as Python, Java, or Scala. Hands‐on experience with big data frameworks (e.g., Spark, Hadoop, Flink) and cloud platforms (AWS, GCP, or Azure). Familiarity with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and workflow orchestration tools (e.g., Airflow, Luigi). ...

Worked with one or more cloud platforms and services (AWS, Azure, GCP) Extensive hands‐on experience with modern data technologies, ETL tools (e.g. Kafka, Flink, DBT etc.), data storage (e.g. Snowflake, Redshift, etc.) and also IaC (e.g. Terraform, CloudFormation) Software development experience with one or more languages (e.g. Python ...

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 ...

Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Google BigQuery, Amazon Redshift Data engineering and orchestration: Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Dataflow, Kafka, Flink Governance, catalogue and lineage: Microsoft Purview, Collibra, Informatica, Alation, Atlan, OpenLineage Graph, ontology and semantic technologies: Neo4j, Amazon Neptune, Stardog, GraphDB, RDF, OWL, SPARQL ...

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 ...

OpenTelemetry Strong problem‐solving skills and a systematic approach to diagnosing and resolving issues Highly Desirable Skills Experience with streaming frameworks such as Flink, Kafka Streams and Kafka Connect Knowledge of modern data lake technologies including Delta Lake, Iceberg and Glue Data Catalog Exposure to DataOps practices and collaboration ...

production Worked with one or more cloud platforms and services (AWS, Azure, GCP) Hands-on experience with modern data technologies and tools (e.g. Kafka, Flink, DBT etc.), data storage (e.g. Snowflake, Redshift, etc.) and also IaC (e.g. Terraform, CloudFormation) Pragmatic approach to solving problems Nice to haves Keen interest ...

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 ...

. Build and maintain platform capabilities supporting batch and real-time data workloads . Develop and operate distributed data services using Kafka, Kinesis, Spark, Flink or equivalent technologies . Build and maintain cloud-native data platform capabilities using AWS and/or Azure . Support data ingestion, processing, storage … experience with real-time streaming and event-driven architectures , including Kafka, Kinesis or equivalent. Experience with distributed data processing technologies such as Spark, Flink, Kafka Streams or equivalent. Strong experience with AWS and/or Azure cloud environments. Experience with cloud services such as S3, Glue, Lambda, RDS, Athena ...

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 ...

SMTs), and converter settings. Administer Schema Registry (compatibility levels, subject naming strategies, serializers/deserializers, schema size & references). Operate ksqlDB and/or Flink for streaming SQL; enforce resource limits and multi tenant governance. Engineer low latency and secure connectivity across data centers/VPCs/VNETs; manage ...

legal advisors to ensure holistic solutions Your areas of knowledge and expertise Proven experience designing and implementing data lakehouse architectures (Databricks, Delta Lake, Apache Flink, or similar technologies) Strong, hands-on AWS cloud experience including services such as S3, Glue, Lake Formation, Athena, and Redshift Demonstrated expertise ...

offerings. Strong programming skills (Python, Java, C++) and experience with DevOps practices (CI/CD). Knowledge of big data technologies (Hadoop, Spark, Flink). Knowledge of NoSQL databases (MongoDB, Cassandra, DynamoDB), message queueing systems (Kafka, RabbitMQ), and version control systems (Git). Preferred Skills: Hugging Face Transformers. Familiarity ...

leakage, transaction costs and changing market conditions. For the Developer track: Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.) Experience with testing, monitoring, and debugging complex systems under load Strong experience with microservices, databases, and production infrastructure We’re people without ...

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 ...

across data pipelines. The ideal candidate has 3+ years in data platform or infrastructure roles, strong AWS and Terraform skills, and experience with Kafka, Flink, Spark, and related lakehouse #J-18808-Ljbffr ...

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 ...