

Eton Solution
Senior Data Engineer – Flink SQL Specialist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer – Flink SQL Specialist, offering a hybrid work location and competitive pay. Requires 8+ years of data engineering experience, deep expertise in Flink SQL, and proficiency in real-time data processing and streaming data formats.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 22, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Bellevue, WA
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🧠 - Skills detailed
#SQL Queries #Cloud #Kafka (Apache Kafka) #Data Processing #Kubernetes #AWS Kinesis #Azure #Data Pipeline #Observability #JSON (JavaScript Object Notation) #Deployment #SQL (Structured Query Language) #Scala #Spark (Apache Spark) #GCP (Google Cloud Platform) #Libraries #Migration #Docker #Data Engineering #AWS (Amazon Web Services) #Apache Kafka #"ETL (Extract #Transform #Load)"
Role description
About the Role:
• Immigration sponsorship is not available in this role
• We are looking for an experienced Data Engineer (8+ years of experience) with deep expertise in Flink SQL to join our engineering team. This role is ideal for someone who thrives on building robust real-time data processing pipelines and has hands-on experience designing and optimizing Flink SQL jobs in a production environment.
You’ll work closely with data engineers, platform teams, and product stakeholders to create scalable, low-latency data solutions that power intelligent applications and dashboards.
⸻
Key Responsibilities:
• Design, develop, and maintain real-time streaming data pipelines using Apache Flink SQL.
• Collaborate with platform engineers to scale and optimize Flink jobs for performance and reliability.
• Build reusable data transformation logic and deploy to production-grade Flink clusters.
• Ensure high availability and correctness of real-time data pipelines.
• Work with product and analytics teams to understand requirements and translate them into Flink SQL jobs.
• Monitor and troubleshoot job failures, backpressure, and latency issues.
• Contribute to internal tooling and libraries that improve Flink developer productivity.
Required Qualifications:
• Deep hands-on experience with Flink SQL and the Apache Flink ecosystem.
• Strong understanding of event time vs processing time semantics, watermarks, and state management.
• 3+ years of experience in data engineering, with strong focus on real-time/streaming data.
• Experience writing complex Flink SQL queries, UDFs, and windowing operations.
• Proficiency in working with streaming data formats such as Avro, Protobuf, or JSON.
• Experience with messaging systems like Apache Kafka or Pulsar.
• Familiarity with containerized deployments (Docker, Kubernetes) and CI/CD pipelines.
• Solid understanding of distributed system design and performance optimization.
Nice to Have:
• Experience with other stream processing frameworks (e.g., Spark Structured Streaming, Kafka Streams).
• Familiarity with cloud-native data stacks (AWS Kinesis, GCP Pub/Sub, Azure Event Hub).
• Experience in building internal tooling for observability or schema evolution.
• Prior contributions to the Apache Flink community or similar open-source projects.
Why Join Us:
• Work on cutting-edge real-time data infrastructure that powers critical business use cases.
• Be part of a high-caliber engineering team with a culture of autonomy and excellence.
• Flexible working arrangements with competitive compensation.
About the Role:
• Immigration sponsorship is not available in this role
• We are looking for an experienced Data Engineer (8+ years of experience) with deep expertise in Flink SQL to join our engineering team. This role is ideal for someone who thrives on building robust real-time data processing pipelines and has hands-on experience designing and optimizing Flink SQL jobs in a production environment.
You’ll work closely with data engineers, platform teams, and product stakeholders to create scalable, low-latency data solutions that power intelligent applications and dashboards.
⸻
Key Responsibilities:
• Design, develop, and maintain real-time streaming data pipelines using Apache Flink SQL.
• Collaborate with platform engineers to scale and optimize Flink jobs for performance and reliability.
• Build reusable data transformation logic and deploy to production-grade Flink clusters.
• Ensure high availability and correctness of real-time data pipelines.
• Work with product and analytics teams to understand requirements and translate them into Flink SQL jobs.
• Monitor and troubleshoot job failures, backpressure, and latency issues.
• Contribute to internal tooling and libraries that improve Flink developer productivity.
Required Qualifications:
• Deep hands-on experience with Flink SQL and the Apache Flink ecosystem.
• Strong understanding of event time vs processing time semantics, watermarks, and state management.
• 3+ years of experience in data engineering, with strong focus on real-time/streaming data.
• Experience writing complex Flink SQL queries, UDFs, and windowing operations.
• Proficiency in working with streaming data formats such as Avro, Protobuf, or JSON.
• Experience with messaging systems like Apache Kafka or Pulsar.
• Familiarity with containerized deployments (Docker, Kubernetes) and CI/CD pipelines.
• Solid understanding of distributed system design and performance optimization.
Nice to Have:
• Experience with other stream processing frameworks (e.g., Spark Structured Streaming, Kafka Streams).
• Familiarity with cloud-native data stacks (AWS Kinesis, GCP Pub/Sub, Azure Event Hub).
• Experience in building internal tooling for observability or schema evolution.
• Prior contributions to the Apache Flink community or similar open-source projects.
Why Join Us:
• Work on cutting-edge real-time data infrastructure that powers critical business use cases.
• Be part of a high-caliber engineering team with a culture of autonomy and excellence.
• Flexible working arrangements with competitive compensation.