数据解决方案工程师
Data Solutions Engineer
作为数据解决方案工程师，你将在为客户提供数据驱动平台的部署、运营和持续改进中发挥关键作用。
你将处于数据工程、系统性能优化和面向客户的工程技术的交汇点，确保我们的AI个性化解决方案在生产环境中可靠运行并带来可衡量的价值。
你将与产品管理、数据科学和客户成功团队紧密合作，并定期与客户的工程技术团队互动。
“个性化挑战”团队目前以欧洲为中心，你将成为第一位北美地区的成员。你将主要通过远程方式与欧洲的直接团队成员沟通，同时也会与位于华盛顿特区、多伦多、杰克逊维尔和芝加哥的北美庞大团队协作。请注意，Eagle Eye在全球均有布局，包括北美、EMEA和亚太地区。
**要求**
**职位分解与重点**
该职位是混合型的：
- 实战数据工程 – 60%
- 数据驱动系统的持续优化 – 30%
- 面向客户的工程技术支持与工单解决 – 10%
此职位的成功由平台可靠性、数据质量、系统性能以及生产问题的长期解决情况来衡量，而非支持工单的数量。
**关键职责**
平台部署与数据集成
- 为新客户提供平台部署和配置
- 将客户的数据管道集成到我们的数据栈中
- 确保输入和输出数据流中的数据质量、一致性和可靠性
生产支持与工单管理
- 调查并解决与数据管道、系统性能和算法行为相关的技术工单
- 作为客户成功团队的技术升级点
- 诊断根本原因，提出修复方案，并确保重复问题的长期预防
持续优化与性能提升
- 使用指标、日志和实验分析系统和算法性能
- 识别优化数据管道、处理逻辑和算法配置的机会
- 与产品和数据科学团队合作，优先级排序并推出改进
- 设计和分析A/B测试以衡量变更的影响
#### 关于你
#### 你具备以下特质
- 有纪律的问题解决者，喜欢深入探究系统行为的“为什么”，以找到长期解决方案。
- 自主工作者，能够独立完成任务并推动项目进展。
查看英文原文
As a Data Solutions Engineer, you will play a key role in deploying, operating, and continuously improving our data-driven platform for our clients.
You will work at the intersection of data engineering, system performance optimization, and client-facing technical operations, ensuring that our AI personalization solution runs reliably in production and delivers measurable value.
You will collaborate closely with Product Managers, Data Science, and Customer Success teams, and regularly interact with client technical teams.
The team “Personalized Challenges” is currently Europe-based and you will be the first North-America based member. You will primarily communicate remotely with your direct team members in Europe but will also collaborate with our extensive team in North America who are based in Washington, DC, Toronto, Jacksonville and Chicago.. Note that overall, Eagle Eye has a global presence, including North America, EMEA and APAC.
**Requirements**
**Role Breakdown & Focus**
This role is intentionally hybrid:
- Hands-on Data Engineering – 60%
- Continuous Optimization of Data-Driven Systems – 30%
- Client-facing Technical Support & Ticket Resolution – 10%
Success in this role is measured by platform reliability, data quality, system performance, and the long-term resolution of production issues, rather than by volume of support tickets.
K **ey responsibilities**
Platform Deployment & Data Integration
- Deploy and configure our platform for new clients
- Integrate client data pipelines into our data stack
- Ensure data quality, consistency, and reliability across incoming and outgoing data flows
Production Support & Ticket Management
- Investigate and resolve technical tickets related to data pipelines, system performance, and algorithm behavior
- Act as a technical escalation point for Customer Success teams
- Diagnose root causes, propose fixes, and ensure long-term prevention of recurring issues
Continuous Optimization & Performance Improvement
- Analyze system and algorithm performance using metrics, logs, and experimentation
- Identify opportunities to optimize data pipelines, processing logic, and algorithm configurations
- Collaborate with Product and Data Science teams to prioritize and roll out improvements
- Design and analyze A/B tests to measure the impact of changes
#### About You
#### You are
- Disciplined problem-solver who enjoys digging into the "why" of system behavior to find long-term solutions.
- An autonomous worker, ready to be the first North American member of the team while maintaining close ties with European colleagues.
- A clear, structured communicator capable of explaining complex technical issues to both engineers and non-technical stakeholders.
- Rigorous and detail-oriented, especially when monitoring production systems and ensuring data integrity.
- Comfortable navigating production incidents and support tickets with a calm, engineering-driven approach.
- Curious and pragmatic, motivated by understanding real-world client use cases and optimizing system performance.
#### You have
- 3–5 years of experience as a Data Engineer or Data Solutions Engineer in a production-heavy environment.
- A Master’s degree (or equivalent) in Computer Science, Data Engineering, or a related field.
- Deep hands-on experience with Python and/or Scala.
- Proven expertise using Spark for large-scale data processing.
- Practical experience building and managing data stacks within Google Cloud Platform (GCP) and BigQuery.
- A solid foundation in data engineering principles, including data pipeline design and system optimization.
- A working knowledge of Data Science and Machine Learning concepts to help bridge the gap between data flows and algorithm performance.
**Benefits**
- A competitive base salary
- Bonus scheme with potential to earn up to 10% of salary dependent on your own personal behaviors, achievement of goals and company revenue targets
- Flexibility to work from home/various office locations
- Generous annual leave package including
- 20 days paid annual leave
- 5 days paid sick leave which if unused gets added to your annual leave the next year
- Contributory 401K Plan
- Support in continuous learning and self-development
- Access to employee assistance program
- Access to the paid Headspace app subscription
- Mental Health First Aiders to support employee’s mental wellbeing
- Employee Resource Groups focused on underrepresented groups in Eagle Eye, including Purple Women
- Charity Committee committed to organizing events throughout the year to raise money for those less privileged
- A friendly, fun, growing team of people who work hard but love to play hard too, with location specific Christmas parties and annual whole company get together hosted in the UK