高级数据工程师 - 数据与人工智能
Senior Data Engineer - Data & AI
高级数据工程师 – 数据与人工智能
EXO ARNVIND 正与瑞典数字医疗和电子商务领域的先驱企业合作，寻找下一位高级数据工程师。
我们的客户正在通过尖端的 AI、自动化和数据驱动的创新，改变数百万人获取基本服务的方式。
这是一个难得的机会，加入一个高影响力的团队，你的工作将直接塑造一家快速成长、使命驱动型组织的未来。如果你是一位经验丰富的数据工程师，热衷于构建可扩展、生产级的数据解决方案，为分析、实验和 AI 提供支持，那么这个职位适合你。
职位机会
作为高级数据工程师，你将在设计、开发和演进端到端数据基础设施方面发挥核心作用，这些基础设施将推动商业智能和机器学习计划。这是一个以产品为导向的职位，你将与 ML 工程师、软件开发人员、产品经理和业务利益相关者紧密合作，确保数据准确、结构良好且可操作——从数据采集到实时仪表板和生产中的 AI 模型。
你将负责整个数据生命周期，从收集和验证到转换和使用，同时推动数据平台的成熟度、可靠性和可扩展性。这是一个参与高可见度项目的机会，这些项目将影响客户体验、运营效率和战略决策——所有工作都在现代云原生环境中进行。
主要职责
- 端到端数据管理：设计、构建和维护用于分析、A/B 测试和 AI/ML 应用的稳健数据管道。确保数据解决方案的长期可持续性和可扩展性，而不仅仅是初始交付。
- 数据建模与分析支持：设计并实现支持业务指标、实验和数据驱动决策的分析数据模型。将复杂的 KPI 转化为可靠、可信的数据结构。
- 实时与事件驱动数据：与软件工程团队合作，开发可扩展、成本高效且具有弹性的实时和事件驱动的数据采集管道。
- 数据质量和可靠性：实施验证框架、质量检查和监控，确保数据新鲜度、数量、模式一致性以及分布。定义并跟踪数据 SLA/SLO，建立数据问题的回填、重新处理和恢复策略。
- 平台成熟度与引擎
查看英文原文
Senior Data Engineer – Data & AI
EXO ARNVIND is partnering with a pioneering leader in Sweden’s digital healthcare and e-commerce sector to find their next Senior Data Engineer.
Our client is transforming how millions of people access essential services through cutting-edge AI, automation, and data-driven innovation.
This is a rare opportunity to join a high-impact team where your work will directly shape the future of a fast-growing, mission-driven organisation. If you’re a seasoned data engineer with a passion for building scalable, production-grade data solutions that power analytics, experimentation, and AI, this role is for you.
The Opportunity
As a Senior Data Engineer, you will play a central role in designing, developing, and evolving end-to-end data infrastructure that fuels both business intelligence and machine learning initiatives. This is a product-focused position where you’ll collaborate closely with ML engineers, software developers, product managers, and business stakeholders to ensure data is accurate, well-structured, and actionable—from ingestion to real-time dashboards and AI models in production.
You’ll own the entire data lifecycle, from collection and validation to transformation and consumption, while driving improvements to the data platform’s maturity, reliability, and scalability. This is a chance to work on high-visibility projects that impact customer experience, operational efficiency, and strategic decision-making—all within a modern, cloud-native environment.
Key Responsibilities
- End-to-End Data Ownership: Architect, build, and maintain robust data pipelines for analytics, A/B testing, and AI/ML applications. Ensure long-term sustainability and scalability of data solutions, not just initial delivery.
- Data Modeling & Analytics Enablement: Design and implement analytical data models that support business metrics, experimentation, and data-driven decision-making. Translate complex KPIs into reliable, trustworthy data structures.
- Real-Time & Event-Driven Data: Partner with software engineering teams to develop scalable, cost-efficient, and resilient real-time and event-driven data ingestion pipelines.
- Data Quality & Reliability: Implement validation frameworks, quality checks, and monitoring for data freshness, volume, schema consistency, and distribution. Define and track data SLAs/SLOs, and establish strategies for backfills, reprocessing, and recovery from data issues.
- Platform Maturity & Engineering Excellence: Contribute to the evolution of the company’s data platform architecture. Enhance standards, tooling, and best practices across the platform, and leverage CI/CD and Infrastructure as Code (IaC) for reliable, automated deployments.
What We’re Looking For
- Proven experience as a Data Engineer, with a track record of building end-to-end data solutions in production environments.
- Deep expertise in data modeling for analytics and data-driven products, with a focus on scalability and usability.
- Hands-on experience with lakehouse architectures and modern analytical data stacks.
- Experience developing pipelines for analytics, testing, and AI/ML use cases.
- Strong ability to interpret business metrics, derive insights, and drive actionable outcomes from data.
- Solid understanding of data quality, validation, and observability principles.
- Familiarity with CI/CD pipelines and Infrastructure as Code.
- A software engineering mindset: clean, maintainable code, testing, version control, and ownership of deliverables.
- Ability to balance rapid delivery with long-term platform maturity and reliability.
- Excellent communication skills and a collaborative, product-oriented approach.
Nice-to-Haves
- Experience with A/B testing platforms or experimentation frameworks.
- Exposure to MLOps or feature store concepts.
- Familiarity with event-driven architectures and streaming systems.
- Experience with AWS and cloud-native data platforms.
- Knowledge of API/Event-first design and Test-Driven Development (TDD).
Why This Role Stands Out
- Meaningful Impact: Work on AI, ML, and automation projects that improve healthcare accessibility and customer experience for millions of users.
- Flat & Agile Culture: Join a dynamic, cross-functional organisation with minimal bureaucracy, where your ideas are heard and your contributions matter.
- Growth & Development: Access ongoing training, mentorship, and opportunities to attend industry conferences. Own projects from concept to deployment and see your work come to life.
- Stability & Vision: Be part of a financially robust, future-focused company with a clear mission and ambitious growth plans.
Interested? Apply now and let us take it from there.
Originally posted on Himalayas