1 to 25 of 39 Permanent Flink Jobs

analytical systems. API & Micro services Architecture: Comfortable working with REST APIs and micro services architectures. Real-time Stream Processing: Understanding of real-time stream processing frameworks (e.g., PubSub, Kafka, Flink, Spark Streaming). BI Tools & Visualisation Platforms: Experience supporting BI tools or visualization platforms (e.g. Looker, Grafana, PowerBI etc.). Data Pipelines & APIs: Experience in building and maintaining both More ❯

maintaining data pipelines. Proficiency in JVM-based languages (Java, Kotlin), ideally combined with Python and experience in Spring Boot Solid understanding of data engineering tools and frameworks, like Spark, Flink, Kafka, dbt, Trino, and Airflow. Hands-on experience with cloud environments (AWS, GCP, or Azure), infrastructure-as-code practices, and ideally container orchestration with Kubernetes. Familiarity with SQL and 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 ❯

Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to have: Experience with dbt, feature stores, or ML pipeline tooling Familiarity with Elasticsearch or real-time analytics (Flink, Materialize) Exposure to eCommerce, marketplace, or transactional environments More ❯

Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to have: Experience with dbt, feature stores, or ML pipeline tooling Familiarity with Elasticsearch or real-time analytics (Flink, Materialize) Exposure to eCommerce, marketplace, or transactional environments More ❯

in data engineering, data architecture, or a similar role, with at least 3 years in a lead capacity. Proficient in SQL, Python, and big data processing frameworks (e.g., Spark, Flink). Strong experience with cloud platforms (AWS, Azure, GCP) and related data services. Hands-on experience with data warehousing tools (e.g., Snowflake, Redshift, BigQuery), Databricks running on multiple cloud More ❯

Strong experience working with SQL and databases/engines such as MySQL, PostgreSQL, SQL Server, Snowflake, Redshift, Presto, etc Experience building ETL and stream processing pipelines using Kafka, Spark, Flink, Airflow/Prefect, etc. Familiarity with data science stack: e.g. Juypter, Pandas, Scikit-learn, Dask, Pytorch, MLFlow, Kubeflow, etc. Strong experience with using AWS/Google Cloud Platform (S3S More ❯

tranformations for production data pipelines. Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches. Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.) Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs. Experience More ❯

and guide implementation teams • Deep understanding of Kafka internals, KRaft architecture, and Confluent components • Experience with Confluent Cloud, Stream Governance, Data Lineage, and RBAC • Expertise in stream processing (Apache Flink, Kafka Streams, ksqlDB) and event-driven architecture • Strong proficiency in Java, Python, or Scala • Proven ability to integrate Kafka with enterprise systems (databases, APIs, microservices) • Hands-on experience with More ❯

and guide implementation teams • Deep understanding of Kafka internals, KRaft architecture, and Confluent components • Experience with Confluent Cloud, Stream Governance, Data Lineage, and RBAC • Expertise in stream processing (Apache Flink, Kafka Streams, ksqlDB) and event-driven architecture • Strong proficiency in Java, Python, or Scala • Proven ability to integrate Kafka with enterprise systems (databases, APIs, microservices) • Hands-on experience with More ❯

Prometheus, Nagios, Telegraf and others. Knowledge and demonstrable hands-on experience with middleware technologies (Kafka, API gateways and others) and Data Engineering tools/frameworks like Apache Spark, Airflow, Flink and Hadoop ecosystems. Understanding of network technology fundamentals, Data Structures, scalable system design and ability to translate information in a structured manner for wider product and engineering teams to More ❯

Azure and distributed systems. Preferred Skills Kubernetes & Helm: Deploying and managing containerized applications at scale with reliability and fault tolerance. Kafka (Confluent): Familiarity with event-driven architectures; experience with Flink or KSQL is a plus. Airflow: Experience configuring, maintaining, and optimizing DAGs. Energy or commodity trading: Understanding the data challenges and workflows in this sector. Trading domain knowledge: Awareness More ❯

Azure and distributed systems. Preferred Skills Kubernetes & Helm: Deploying and managing containerized applications at scale with reliability and fault tolerance. Kafka (Confluent): Familiarity with event-driven architectures; experience with Flink or KSQL is a plus. Airflow: Experience configuring, maintaining, and optimizing DAGs. Energy or commodity trading: Understanding the data challenges and workflows in this sector. Trading domain knowledge: Awareness More ❯

pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to create meaningful business impact. Soft Skills: Excellent communication and More ❯

working with cloud platforms such as AWS, Azure, or GCP. Exposure to modern data tools such as Snowflake, Databricks, or BigQuery. Familiarity with streaming technologies (e.g., Kafka, Spark Streaming, Flink) is an advantage. Experience with orchestration and infrastructure tools such as Airflow, dbt, Prefect, CI/CD pipelines, and Terraform. What you get in return: Up to 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 ❯

GitHub Actions, AWS CodePipeline). Desirable Skills Experience with containerization (Docker, Kubernetes, ECS/EKS). Familiarity with data platforms (Redshift, Snowflake). Exposure to streaming technologies (Kafka, Apache Flink). Knowledge of ETL environments and data migration . AWS certifications (Solutions Architect, SysOps, DevOps Engineer). Qualifications Degree in Computer Science, Engineering, or equivalent experience. AWS Certified Solutions More ❯

or similar) from a good University highly desirable. Nice to Have: Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Experience with real-time streaming technologies (Kafka, Apache Storm). Understanding of infrastructure More ❯

contract definition, clean code, CI/CD, path to production Worked with AWS as a cloud platform 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, Java, Scala, Go ) Pragmatic approach More ❯

Java, Scala). Experience working in financial services or large enterprise environments. Demonstrated ability to lead distributed engineering teams effectively. Deep understanding of data architecture, streaming technologies (e.g., Kafka, Flink), and cloud platforms (e.g., AWS, Azure, GCP). Excellent communication and stakeholder management skills. ABOUT CAPGEMINI Capgemini is a global business and technology transformation partner, helping organizations to accelerate More ❯

Java, Scala). Experience working in financial services or large enterprise environments. Demonstrated ability to lead distributed engineering teams effectively. Deep understanding of data architecture, streaming technologies (e.g., Kafka, Flink), and cloud platforms (e.g., AWS, Azure, GCP). Excellent communication and stakeholder management skills. ABOUT CAPGEMINI Capgemini is a global business and technology transformation partner, helping organizations to accelerate More ❯

Java, data structures and concurrency, 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 services, deployments, stateful sets etc. More ❯

about complex problems at high scale. Ability to work collaboratively in a team environment and communicate effectively with other teams across Cloudflare. Experience with data streaming technologies (e.g., Kafka, Flink) is a strong plus. Experience with various logging platforms or SIEMs (e.g., Splunk, Datadog, Sumo Logic) and storage destinations (e.g., S3, R2, GCS) is a plus. Experience with Infrastructure More ❯

to Date with Technology: Keep yourself and the team updated on the latest Python technologies, frameworks, and tools like Apache Spark, Databricks, Apache Pulsar, Apache Airflow, Temporal, and Apache Flink, sharing knowledge and suggesting improvements. Documentation: Contribute to clear and concise documentation for software, processes, and systems to ensure team alignment and knowledge sharing. Your Qualifications Experience: Professional experience … pipelines, and machine learning workflows. Workflow Orchestration: Familiarity with tools like Apache Airflow or Temporal for managing workflows and scheduling jobs in distributed systems. Stream Processing: Experience with Apache Flink or other stream processing frameworks is a plus. Desired Skills Asynchronous Programming: Familiarity with asynchronous programming tools like Celery or asyncio. Frontend Knowledge: Exposure to frontend frameworks like React More ❯

Java – if you haven’t been siloed in a big firm then don’t worry. Additional exposure to the following is desired : - Tech Stack you will learn Hadoop and Flink RUST, Javascript, React, Redux, Flow Linux, Jenkins Kafka, Avro, Kubernetes, Puppet Involvement in the Java community My client is based London. Home work is encouraged but you will need More ❯