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Data Engineer Flink Jobs in Arizona (NOW HIRING)

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 ... Responsibilities : • Build and optimize real-time and batch data processing solutions using ...

... 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 ...

Proficiency in big data, the use of frameworks related to stream computing, such as Spark, Flink ... excellent engineering practice capabilities * Experience in algorithms such as, anti-fraud ...

Showing results 21-28

Data Engineer Flink information

What is a data engineer Flink?

A Data Engineer Flink is a data engineering professional who specializes in using Apache Flink, an open-source stream processing framework, to build, maintain, and optimize systems that process large-scale data in real time. They design and implement data pipelines, ensure data quality and consistency, and collaborate with other engineering teams to deliver reliable and scalable data solutions. Their expertise allows organizations to process, analyze, and react to data as it is generated, enabling real-time insights and decision-making.

What are the key skills and qualifications needed to thrive as a data engineer Flink?

To thrive as a Data Engineer specializing in Flink, you need strong programming skills (especially in Java or Scala), a solid understanding of distributed data processing, and experience with data architecture. Familiarity with Apache Flink, stream processing frameworks, big data tools (like Kafka, Hadoop, or Spark), and cloud platforms is typically required, along with relevant certifications. Excellent problem-solving abilities, attention to detail, and effective teamwork and communication skills help you excel in complex data environments. These competencies are crucial for building reliable, scalable data pipelines that power real-time analytics and business decision-making.

What are some common challenges data engineers face when working with Apache Flink in a production environment?

Data Engineers working with Apache Flink often encounter challenges such as managing stateful stream processing at scale, ensuring fault tolerance, and optimizing resource usage for real-time data pipelines. Handling late-arriving data and tuning Flink jobs for low latency and high throughput are also frequent hurdles. Collaborating closely with data scientists and application developers is key to aligning data models and ensuring smooth data flow throughout the system.

Are data engineers still in demand?

Data engineers, including those skilled in Apache Flink, are in high demand due to the increasing need for real-time data processing and scalable data infrastructure. Organizations seek professionals with expertise in big data tools, cloud platforms, and programming languages like Java or Scala to build and maintain data pipelines. The role is expected to grow as data-driven decision-making becomes more critical across industries.

What are popular job titles related to Data Engineer Flink jobs in Arizona?

For Data Engineer Flink jobs in Arizona, the most frequently searched job titles are:

What cities in Arizona are hiring for Data Engineer Flink jobs?

Cities in Arizona with the most Data Engineer Flink job openings:

Senior MLOps Engineer - USA Onsite (Scottsdale, AZ)

S27a

Scottsdale, AZ • On-site

$170 - $250/hr

Other

Medical, Dental, Vision, Life, PTO

This job post has expired today. Applications are no longer accepted.


Job description

About the Role

We are looking for a Senior AI/ML Engineer to lead the design and delivery of production-grade machine learning systems and drive the maturity of our ML engineering and MLOps capabilities. In this role, you will own critical ML workstreams end to end, make key architectural decisions, mentor other engineers, and collaborate closely with cross-functional teams to ensure ML solutions are scalable, reliable, and aligned with business objectives. The ideal candidate brings deep technical expertise, proven production experience, and the ability to influence technical direction across the team.

Key Responsibilities
  • Lead the design, development, and production deployment of complex machine learning systems across multiple domains (NLP, computer vision, recommendation, forecasting, etc.).
  • Own the end-to-end ML lifecycle from problem framing and data strategy through model development, validation, deployment, and monitoring.
  • Architect scalable, fault-tolerant ML pipelines using modern orchestration and serving frameworks.
  • Drive the adoption and maturity of MLOps practices including CI/CD for ML, automated retraining, model registry, and governance.
  • Define and enforce engineering standards for model development, testing, code quality, and documentation.
  • Evaluate and introduce new tools, frameworks, and techniques to improve model performance, pipeline efficiency, and developer productivity.
  • Collaborate with data engineers, platform engineers, and product teams to align ML infrastructure with organizational goals.
  • Mentor and provide technical guidance to mid-level and junior engineers.
  • Conduct design reviews, code reviews, and architectural assessments for ML systems.
  • Contribute to technical roadmap planning and communicate tradeoffs and recommendations to engineering leadership.
  • Identify and mitigate risks related to data quality, model drift, bias, and security in production ML systems.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field. PhD is a plus.
  • 8-10 years of professional experience in ML engineering, applied ML research, or a closely related role with significant production delivery.
  • Deep expertise in Python and advanced proficiency with ML frameworks such as TensorFlow, PyTorch, or JAX.
  • Extensive experience designing and operating production ML pipelines at scale.
  • Strong knowledge of MLOps principles and tools including MLflow, Kubeflow, Airflow, Argo Workflows, or similar.
  • Proven experience with cloud-native ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and infrastructure-as-code practices.
  • Experience with model serving at scale using frameworks such as TensorFlow Serving, Triton, BentoML, or Seldon.
  • Strong understanding of distributed computing, data engineering, and scalable system design.
  • Experience with monitoring, observability, and governance for production ML systems.
  • Demonstrated ability to mentor engineers and influence technical direction.
  • Excellent communication skills with the ability to present technical concepts to both technical and non-technical audiences.
Preferred Qualifications
  • Experience with LLM-based systems, RAG pipelines, or agentic AI architectures.
  • Experience with feature platforms (Feast, Tecton) and data quality frameworks (Great Expectations, Deequ).
  • Familiarity with model explainability and fairness tools (SHAP, LIME, Fairlearn).
  • Experience with real-time ML serving and streaming data pipelines (Kafka, Flink).
  • Contributions to open-source ML/MLOps projects.
  • Experience with GPU cluster management and cost optimization for training workloads.
Perks And Benefits Of Working With Us
  • Unlimited PTO.
  • Please ask us about our very generous parental leave, much above industry standards!.
  • Entrepreneurial culture where pushing limits and taking risks is everyday business.
  • Open communication with management and company leadership.
  • Small, dynamic teams = massive impact.
  • Medical, Dental and Vision coverage for employees.
  • Access to Disability & Life insurance.
  • Mental health and wellbeing support
  • Annual bonus program
  • Employer Stock Purchase Program (ESPP)
  • Yearly Team building experiences
  • Mentorship and sponsorship opportunities
  • Manager resources and support

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.

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