$57.75 - $76.75/hr
Exposure to cutting-edge AI and big data infrastructure (Spark, Kafka, ScyllaDB, Flink). Employment Type: FULL_TIME
$57.75 - $76.75/hr
Exposure to cutting-edge AI and big data infrastructure (Spark, Kafka, ScyllaDB, Flink). Employment Type: FULL_TIME
Experience with with streaming frameworks such as Apache Flink or Google Cloud Dataflow * Experience with NoSQL databases such as Bigtable, Cassandra Staff Software Engineer (IV): Includes all the ...
Experience with with streaming frameworks such as Apache Flink or Google Cloud Dataflow * Experience with NoSQL databases such as Bigtable, Cassandra Staff Software Engineer (IV): Includes all the ...
Flink information
See Utah salary details
$9.19 - $15.42
6% of jobs
$15.42 - $21.65
0% of jobs
$21.65 - $27.87
0% of jobs
$27.87 - $34.10
0% of jobs
$34.10 - $40.33
4% of jobs
$44.40 is the 25th percentile. Wages below this are outliers.
$40.33 - $46.55
22% of jobs
$46.55 - $52.78
14% of jobs
The median wage is $53.62 / hr.
$52.78 - $59.01
27% of jobs
$59.66 is the 75th percentile. Wages above this are outliers.
$59.01 - $65.23
13% of jobs
$65.23 - $71.46
11% of jobs
$71.46 - $77.69
3% of jobs
$9
$52
$77
How much do flink jobs pay per hour?
As of Aug 7, 2026, the average hourly pay for flink in Utah is $52.58, according to ZipRecruiter salary data. Most workers in this role earn between $44.18 and $61.30 per hour, depending on experience, location, and employer.
What are Flink jobs?
Flink jobs are user-defined programs that run on Apache Flink, an open-source stream processing framework. These jobs process data in real-time or in batches, allowing organizations to analyze, transform, or aggregate large volumes of data efficiently. Flink jobs are written in languages like Java, Scala, or Python and can be used for a variety of applications such as event-driven analytics, real-time monitoring, and data pipeline processing. They can be deployed on clusters to handle large-scale data processing with low latency and high throughput.
How to start a Flink job?
To start a Flink job, you need to package your application as a JAR file and submit it to a Flink cluster using the command line interface, typically with the 'flink run' command. Ensure your environment is set up with Java and Flink installed, and that your job code is properly configured for the cluster environment. Monitoring and debugging can be done through Flink's web dashboard or logs.
What is the difference between Flink vs Kafka Streams?
| Aspect | Flink | Kafka Streams |
|---|---|---|
| Primary Use | Distributed stream processing framework for large-scale data processing | Client library for real-time stream processing within Kafka |
| Deployment Environment | Cluster-based, supports standalone and cloud deployments | Embedded within Java applications, runs on client machines |
| Complexity | Requires setup of cluster and infrastructure | Simpler to integrate with existing Kafka setup |
| Use Cases | Complex event processing, large-scale analytics | Real-time data transformation, lightweight processing |
Flink and Kafka Streams are both popular stream processing tools, but Flink is suited for large-scale, complex processing across clusters, while Kafka Streams is ideal for lightweight, real-time processing within Kafka environments. Your choice depends on processing complexity and deployment needs.
What are some common challenges faced by Apache Flink developers and how can they be overcome?
Apache Flink developers often encounter challenges such as handling stateful stream processing at scale, ensuring low-latency data flows, and managing the complexities of distributed systems. Addressing these issues typically involves careful job design, leveraging Flink's checkpointing and state management features, and optimizing resource allocation. Collaborating closely with DevOps and data engineering teams can also help in troubleshooting deployment and performance bottlenecks, ensuring smooth operation in production environments.
What is a Flink job?
A Flink job is a program written using Apache Flink, an open-source framework for distributed stream and batch data processing. It involves defining data sources, transformations, and sinks to process large-scale data in real-time or batch mode, often requiring knowledge of Java or Scala and familiarity with Flink's APIs and environment.
What are the key skills and qualifications needed to thrive as an Apache Flink developer?
To thrive as an Apache Flink Developer, you need strong programming skills (typically in Java or Scala), a solid understanding of distributed systems, and experience with real-time data processing frameworks, preferably backed by a relevant degree in computer science or engineering. Familiarity with Flink’s APIs, stream processing concepts, and integration with tools like Kafka, Hadoop, or AWS, as well as certifications in big data technologies, are highly valuable. Analytical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating with teams and troubleshooting complex data workflows. These skills are crucial for building scalable, reliable, and efficient data pipelines that drive real-time analytics and business decisions.
What does Flink do?
A Flink job involves developing and maintaining real-time data processing applications using Apache Flink, an open-source stream processing framework. It requires skills in Java or Scala, understanding of distributed systems, and familiarity with data streaming concepts to efficiently process large-scale data in real-time environments.
What are popular job titles related to Flink jobs in Utah? For Flink jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Flink jobs in Utah look for? The top searched job categories for Flink jobs in Utah are:
$57.75 - $76.75/hr
Full-time
Re-posted 21 days ago
Job description
Position Overview
Job Title: Site Reliability Engineer (SRE)
Department: Technology
Location: Manila
Reporting To: Head of Infra
Tookitaki is looking for a Site Reliability Engineer (SRE) with 3–6 years of experience to help maintain and scale the infrastructure that powers our flagship products—FinCense and the AFC Ecosystem. As an SRE, you will work at the intersection of software engineering and infrastructure, ensuring high availability, performance, and scalability of our platforms.
You will collaborate with engineering, DevOps, and client success teams to operationalize deployments across on-premise, VPC, and Compliance as a Service (CaaS) environments while improving monitoring, automation, and incident response.
Position PurposeThe SRE role is responsible for ensuring the reliability and efficiency of Tookitaki’s production systems and environments. This includes building monitoring systems, improving deployment pipelines, automating routine operations, and responding to production incidents. You’ll help build a resilient infrastructure that supports our mission to provide AI-driven solutions that prevent financial crime.
Key ResponsibilitiesSystem Monitoring & Incident Management
Build and maintain monitoring, alerting, and logging systems using tools like Prometheus, Grafana, and ELK.
Respond to incidents and outages, conduct post-mortems, and implement corrective actions.
Infrastructure & Deployment Automation
Automate infrastructure provisioning and application deployment using Terraform, Ansible, or Helm.
Contribute to CI/CD pipelines, improve reliability and speed of software delivery (GitLab CI, Jenkins, etc.).
Container & Orchestration Management
Manage and troubleshoot Docker containers and Kubernetes clusters, ensuring workload scaling, resource management, and health.
Support application updates, rollbacks, and blue-green or canary deployments.
Cloud & Platform Operations
Operate within AWS (preferred) or GCP environments (EC2, S3, VPC, IAM).
Monitor system availability and resource usage across environments.
Security & Reliability Enhancements
Implement and monitor TLS/SSL, RBAC, SSO, and secure API practices.
Support compliance and security audit activities by maintaining logs, access controls, and operational hygiene.
Collaboration & Documentation
Work closely with developers, infra engineers, and support teams to ensure production readiness.
Maintain playbooks, runbooks, and system documentation for reliability engineering activities.
Bachelor’s degree in Computer Science, Engineering, or related technical field.
3–6 years in Site Reliability Engineering, DevOps, Platform Engineering, or a related role.
Experience with production environments and live system debugging.
Kubernetes, Docker, Helm – experience deploying and scaling services.
Linux administration and command-line debugging.
Hands-on with AWS (preferred) or GCP cloud platforms.
Scripting in Bash and Python for automation and monitoring tasks.
Experience with monitoring and alerting tools like Prometheus, Grafana, ELK, or Datadog.
Familiarity with databases (e.g., MariaDB, ScyllaDB) and SQL/CQL querying.
Strong problem-solving and debugging skills.
Ability to work in on-call rotations and high-pressure production environments.
Excellent communication and documentation abilities.
Operational Reliability: Ensures system uptime and performance through proactive monitoring and maintenance.
Automation Mindset: Reduces manual effort through scripting and tooling.
Incident Response: Quick identification and resolution of issues to minimize downtime.
Cross-Functional Collaboration: Works effectively with engineering, support, and infra teams.
Security Awareness: Applies best practices in infrastructure and platform security.
Maintain 99.9%+ uptime across production environments.
Reduce mean time to detect (MTTD) and mean time to resolve (MTTR) for critical incidents.
Increase in automation coverage and reduction in manual deployment steps.
High internal satisfaction from developers on CI/CD and platform reliability.
Compliance readiness and security log availability for audits.
Competitive compensation
Work on a globally recognized RegTech platform transforming financial crime prevention.
Exposure to cutting-edge AI and big data infrastructure (Spark, Kafka, ScyllaDB, Flink).
Employment Type: FULL_TIME