Eton Solution

Staff Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Staff Data Engineer with 8+ years of experience, specializing in Flink SQL, to design and maintain real-time data pipelines. Contract length is unspecified, pay rate is competitive, and the work location is hybrid.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
November 18, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Bellevue, WA
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🧠 - Skills detailed
#Azure #Apache Kafka #Libraries #Migration #AWS Kinesis #SQL (Structured Query Language) #GCP (Google Cloud Platform) #Kubernetes #SQL Queries #AWS (Amazon Web Services) #Observability #Data Processing #"ETL (Extract #Transform #Load)" #Cloud #Kafka (Apache Kafka) #Scala #Docker #Deployment #JSON (JavaScript Object Notation) #Spark (Apache Spark) #Data Engineering #Data Pipeline
Role description
β€’ Immigration sponsorship is not available in this role β€’ 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. βΈ» Key Responsibilities: β€’ Design, develop, and maintain real-time streaming data pipelines using Apache Flink SQL. β€’ Collaborate with platform engineers to scale and optimize Flink jobs for performance and reliability. β€’ Build reusable data transformation logic and deploy to production-grade Flink clusters. β€’ Ensure high availability and correctness of real-time data pipelines. β€’ Work with product and analytics teams to understand requirements and translate them into Flink SQL jobs. β€’ Monitor and troubleshoot job failures, backpressure, and latency issues. β€’ Contribute to internal tooling and libraries that improve Flink developer productivity. Required Qualifications: β€’ Deep hands-on experience with Flink SQL and the Apache Flink ecosystem. β€’ Strong understanding of event time vs processing time semantics, watermarks, and state management. β€’ 3+ years of experience in data engineering, with strong focus on real-time/streaming data. β€’ Experience writing complex Flink SQL queries, UDFs, and windowing operations. β€’ Proficiency in working with streaming data formats such as Avro, Protobuf, or JSON. β€’ Experience with messaging systems like Apache Kafka or Pulsar. β€’ Familiarity with containerized deployments (Docker, Kubernetes) and CI/CD pipelines. β€’ Solid understanding of distributed system design and performance optimization. Nice to Have: β€’ Experience with other stream processing frameworks (e.g., Spark Structured Streaming, Kafka Streams). β€’ Familiarity with cloud-native data stacks (AWS Kinesis, GCP Pub/Sub, Azure Event Hub). β€’ Experience in building internal tooling for observability or schema evolution. β€’ Prior contributions to the Apache Flink community or similar open-source projects. Why Join Us: β€’ Work on cutting-edge real-time data infrastructure that powers critical business use cases. β€’ Be part of a high-caliber engineering team with a culture of autonomy and excellence. β€’ Flexible working arrangements with competitive compensation.