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Flink Jobs in Arizona (NOW HIRING)

Description Principal Data Engineer - Real-Time Streaming (Flink) Role Summary As a Principal Data Engineer (Real-Time Streaming - Flink), you will be chartered with designing, developing, and ...

Technology Architect | Java | Apache

Phoenix, AZ · On-site

$62.50 - $84.50/hr

They are seeking an experienced Lead Kafka/Flink Developer to design, build, and support scalable enterprise and cloud-native applications, leveraging strong expertise in Java and event-driven ...

Java AI Developer - Backend AI

Phoenix, AZ · On-site

$50.25 - $65/hr

Develop data pipelines and real-time processing using Flink * Integrate AI and conversational platforms into backend systems * Design and build RESTful APIs and microservices * Collaborate with ...

Software Engineer

Phoenix, AZ · On-site

$52 - $57/hr

Develop and operationalize cloud-native data pipelines using Spark, Kafka, Flink, and related technologies. * Leverage AI and agentic frameworks to automate data management, governance, quality ...

Experience with Flink for stream processing and data pipelines. * Proficiency in Redis for caching and performance optimization. * Database expertise in both MongoDB (NoSQL) and Oracle (RDBMS)

Software Engineer 4

Chandler, AZ · On-site

$69 - $74/hr

Apache Flink * Spark Streaming Preferred Qualifications * Experience building AI-driven automation capabilities for enterprise data platforms. * Knowledge of cybersecurity data ecosystems and ...

Proficiency in big data, the use of frameworks related to stream computing, such as Spark, Flink, etc. And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc. * The basic ...

Proficiency in big data, the use of frameworks related to stream computing, such as Spark, Flink, etc. And familiar with machine learning platforms Tensorflow, Pytorch, Mxnet, etc. * The basic ...

... Flink, Postgres, or similar data technologies * 1+ Years supporting and monitoring service load balancing architectures including F5 & VMware AVI Hard Skills: * Site Reliability Engineer (SRE) Skills ...

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Flink information

See Arizona salary details

$9

$53

$79

How much do flink jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for flink in Arizona is $53.82, according to ZipRecruiter salary data. Most workers in this role earn between $45.24 and $62.74 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?

AspectFlinkKafka Streams
Primary UseDistributed stream processing framework for large-scale data processingClient library for real-time stream processing within Kafka
Deployment EnvironmentCluster-based, supports standalone and cloud deploymentsEmbedded within Java applications, runs on client machines
ComplexityRequires setup of cluster and infrastructureSimpler to integrate with existing Kafka setup
Use CasesComplex event processing, large-scale analyticsReal-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 Arizona? For Flink jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Flink jobs in Arizona look for? The top searched job categories for Flink jobs in Arizona are:
What cities in Arizona are hiring for Flink jobs? Cities in Arizona with the most Flink job openings:
Infographic showing various Flink job openings in Arizona as of August 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $111,946 per year, or $53.8 per hour.

Principal Data Engineer - FLINK

Citizens

Phoenix, AZ

Full-time

Re-posted 16 days ago


Job description

Description

Principal Data Engineer - Real-Time Streaming (Flink)

Role Summary

As a Principal Data Engineer (Real-Time Streaming - Flink), you will be chartered with designing, developing, and operating real-time data systems that drive critical business outcomes. You will lead a team of data engineers and partner with stakeholders to build scalable, event-driven streaming architectures that enable low-latency data access across Citizens business operations.

In addition to core data engineering responsibilities, this role emphasizes Flink-based streaming platforms, event-driven data flow, and highly resilient distributed systems, ensuring that data is continuously processed, governed, and made actionable in near real time.

Specialized Responsibilities

  • Serve as a key contributor to the development of real-time data solutions, partnering with stakeholders to define streaming use cases, SLAs, and latency expectations. 
  • Design and implement event-driven streaming architectures using  Flink and related ecosystem technologies.
  • Engineer and optimize low-latency, high-throughput data pipelines for operational and analytical workloads.
  • Develop and maintain stateful stream processing applications, including windowing, joins, aggregations, and complex event processing.
  • Continuously assess data flow across systems, identifying latency bottlenecks, failure points, and data integrity risks, with a focus on real-time processing gaps. 
  • Implement observability, monitoring, and alerting for streaming systems to ensure availability, performance, and SLA adherence.
  • Ensure operational resiliency and stability, including checkpointing, fault tolerance, exactly-once semantics, and recovery strategies in Flink pipelines.
  • Lead the development of streaming data models and schemas aligned to business outcomes and event contracts. 
  • Govern and evolve event schemas and contracts to support enterprise-wide interoperability and data consistency.
  • Guide engineering teams on best practices for distributed streaming systems, including back-pressure management, scaling, and partitioning strategies.
  • Partner with architecture and platform teams to define standards for real-time data platforms, security, and regulatory compliance within a banking environment.
  • Mentor engineers and drive adoption of streaming-first design patterns within Agile delivery teams.

Preferred Technical Expertise

  • Advanced expertise in  Flink 
  • Strong experience with event streaming platforms
  • Deep understanding of distributed systems design, including fault tolerance, scaling, and high availability
  • Experience building stateful stream processing pipelines with windowing, joins, and event-time processing
  • Proficiency in low-latency pipeline design and performance optimization
  • Experience with cloud-native streaming architectures 
  • Strong programming skills in Java, Scala, and/or Python with streaming frameworks 
  • Familiarity with schema management 
  • Experience integrating streaming data with downstream systems (data lakes, data warehouses, APIs, analytics platforms)
  • Knowledge of real-time analytics and monitoring tools 
  • Understanding of data governance, lineage, and compliance in real-time data environments

Business Outcomes and Impact

  • Enable real-time decision-making across banking operations
  • Reduce data latency from hours to seconds/minutes, improving responsiveness of business processes
  • Improve data reliability and trust through resilient, fault-tolerant streaming pipelines
  • Support digital and event-driven business models, including real-time customer experiences
  • Increase operational efficiency by unifying batch and streaming data architectures
  • Strengthen regulatory and risk capabilities through timely and accurate data availability
  • Drive enterprise scalability, enabling growth in transaction volumes and data complexity

Preferred Qualifications

  • 8+ years of data engineering experience with demonstrated leadership in streaming data platforms 
  • Hands-on experience implementing  Flink in production environments
  • Experience in financial services or banking, with understanding of real-time data use cases such as payments, fraud, or trading 
  • Experience managing or mentoring engineering teams in Agile delivery environments 
  • Familiarity with machine learning integration in streaming pipelines (real-time scoring/inference) 
  • Experience with BI and analytics tools to consume streaming outputs 
  • Bachelor's degree required; Master's preferred in Computer Science, Engineering, or related discipline 
  • Certifications in Big Data, AWS, Streaming Technologies, or Agile methodologies preferred 

Modernization and Architecture Expectations

  • Champion shift from batch-centric architectures to event-driven, streaming-first platforms
  • Define and implement enterprise streaming architecture patterns 
  • Establish standards for data contracts, schema evolution, and event governance
  • Build scalable, cloud-native streaming platforms aligned to enterprise architecture strategy
  • Integrate streaming with AI/ML platforms to enable real-time inference and intelligent automation
  • Drive platform reliability and engineering maturity, including automated testing, CI/CD, and infrastructure-as-code for streaming pipelines
  • Promote reusability and modular design in streaming components to accelerate delivery across teams
  • Ensure all solutions meet security, compliance, and risk requirements specific to financial institutions

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Education:Why Work for UsEmployment Type: 1ST