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Intern Streaming Data Engineer 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 ...

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 ...

Data Engineer

Scottsdale, AZ · On-site

$114K - $137K/yr

The Data Engineer designs, builds, and maintains scalable data integration pipelines and ... Experience working with APIs, file-based ingestion, and streaming data sources * Knowledge of data ...

Data Engineer

Scottsdale, AZ · On-site

$114K - $137K/yr

The Data Engineer designs, builds, and maintains scalable data integration pipelines and ... Experience working with APIs, file-based ingestion, and streaming data sources * Knowledge of data ...

Description Principal Data Engineer - Graph Data Engineering Neo4j Role Summary As Principal Data ... Build and optimize graph ingestion pipelines for batch and streaming data sources, ensuring data ...

Description Principal Data Engineer - Graph Data Engineering Neo4j Role Summary As Principal Data ... Build and optimize graph ingestion pipelines for batch and streaming data sources, ensuring data ...

Senior Data Engineer

Scottsdale, AZ

$106K - $145K/yr

Spearheads efforts with multiple, disparate, data providers, as well as downstream consumers, to engineer efficient, tracable, and fault tolerant, batch and streaming, data pipelines to that support ...

Data Engineer

Scottsdale, AZ · On-site

$115K - $138K/yr

Job Title: - Data Engineer Location: - Scottsdale AZ (Day 1 Onsite) Job Type: - Contract ***Note ... Knowledge of streaming frameworks (Spark Streaming, Kafka Streams). * Good to have - Aerospike ...

Data Engineer

Phoenix, AZ

$113K - $136K/yr

Data Engineer Location Hyderabad, India (Hybrid) Employment Type Full-Time Experience 3-7 Years ... Experience with streaming platforms like Kafka. * Knowledge of DevOps and Infrastructure as Code.

Senior Data & AI Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

OneLake, Lakehouses, Warehouses, and Data Engineering pipelines). • Build robust ingestion frameworks for batch and streaming data (e.g., ADLS, EventHub, APIs, SFTP) with lineage and governance ...

Data Engineer

Tempe, AZ · On-site +1

$174K - $261K/yr

Your work will power access to data for a variety of use-cases, be it real-time stream processing ... The day-to-day In this Software Engineer role, you will own core components of data ingestion and ...

Data Engineer III

Chandler, AZ · On-site

$116K - $140K/yr

Data Engineer III Job Locations US-AZ-Chandler Job ID 2026-4932 Category Engineering Worker ... Experience with data pipeline design, data modeling, streaming and batch ingestion technologies ...

Big Data Engineer with Java

Phoenix, AZ · On-site

$54.25 - $71.75/hr

Experience with both Streaming and Batch Data Ingestion (Lambda) * Experience with Java * Must have ... The Data Engineer II is responsible for partnering with business unit leaders within NCR to analyze ...

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Lead Data & AI Engineer Location: Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay ... and streaming data sources such as APIs, ADLS, SFTP, and event streams with full lineage and ...

Data Engineer

Scottsdale, AZ · On-site

$60 - $70/hr

Data Engineer Location: Scottsdale, AZ Remote: NO Length: 6 months (potential contract to hire ... Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.

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Intern Streaming Data Engineer information

What is the difference between Intern Streaming Data Engineer vs Intern Data Analyst?

AspectIntern Streaming Data EngineerIntern Data Analyst
Required SkillsKnowledge of streaming platforms (e.g., Kafka, Spark Streaming), programming (Python, Java), data pipeline developmentData analysis, SQL, Excel, basic statistical skills
Work EnvironmentDeveloping real-time data pipelines, working with big data toolsAnalyzing stored data, generating reports and insights
Industry UsageTech, finance, e-commerce companies focusing on real-time data processingMarketing, business intelligence, research departments

The Intern Streaming Data Engineer focuses on building and maintaining real-time data pipelines using streaming technologies, requiring programming and big data skills. In contrast, the Intern Data Analyst primarily analyzes stored data to generate insights, emphasizing statistical and reporting skills. Both roles are common in data-driven industries but serve different functions within data management and analysis.

What does an Intern Streaming Data Engineer do?

An Intern Streaming Data Engineer assists in designing, developing, and maintaining systems that process real-time data streams. They typically work with technologies like Apache Kafka, Apache Flink, or Spark Streaming to collect, process, and analyze data as it arrives. Their responsibilities may include writing code, troubleshooting data pipelines, and collaborating with senior engineers to ensure data flows efficiently. The role is ideal for students or recent graduates looking to gain hands-on experience with big data and real-time analytics.

What types of projects or tasks can an Intern Streaming Data Engineer expect to work on during their internship?

As an Intern Streaming Data Engineer, you can expect to work on projects involving the development, testing, and optimization of real-time data pipelines. Typical tasks may include assisting with the integration of streaming platforms like Apache Kafka or AWS Kinesis, writing and debugging code to process large volumes of incoming data, and collaborating with senior engineers to ensure data quality and reliability. You'll often work within a team of data engineers and analysts, gaining hands-on experience with the latest big data tools and contributing to solutions that support real-time analytics and business decision-making.

What are the key skills and qualifications needed to thrive as an Intern Streaming Data Engineer, and why are they important?

To thrive as an Intern Streaming Data Engineer, you typically need foundational knowledge in computer science, data engineering concepts, and familiarity with real-time data processing. Experience with tools like Apache Kafka, Apache Flink, or Spark Streaming, and programming languages such as Python or Java, is often preferred. Strong problem-solving skills, attention to detail, and effective teamwork and communication abilities help set candidates apart. These skills and qualifications are crucial for efficiently building, maintaining, and troubleshooting streaming data pipelines in dynamic data-driven environments.
What are popular job titles related to Intern Streaming Data Engineer jobs in Arizona? For Intern Streaming Data Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Intern Streaming Data Engineer jobs in Arizona look for? The top searched job categories for Intern Streaming Data Engineer jobs in Arizona are:
Principal Data Engineer - FLINK

Principal Data Engineer - FLINK

Citizens

Phoenix, AZ • On-site

Other

Posted 19 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