1 to 25 of 84 Permanent Flink Jobs

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

e.g., Hadoop, Spark). Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow etc Good knowledge of stream and batch processing solutions like Apache Flink, Apache Kafka Good knowledge of log management, monitoring, and analytics solutions like Splunk, Elastic Stack, New Relic etc Given that this is just a short snapshot of the role More ❯

technologies (e.g., Hadoop, Spark). Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow Good knowledge of stream and batch processing solutions like Apache Flink, Apache Kafka Good knowledge of log management, monitoring, and analytics solutions like Splunk, Elastic Stack, New Relic Note: The following line contains removed formatting for safety. Given that this 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 ❯

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 ❯

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 ❯

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 ❯

power segmentation, recommendation, targeting, and measurement. Strong knowledge of both SQL and NoSQL databases like PostgreSQL, BigQuery, Cassandra, or DynamoDB. Experience with large-scale data platforms (e.g., Spark, Kafka, Flink, BigQuery) and cloud environments, with a preference for AWS or GCP . Expertise in data engineering: pipelines , modeling, batch vs. event streaming, and ETL/ELT. Demonstrated 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯