出海雷达

数据工程师II

Data Engineer II

开发工程限定地区(需当地身份)
公司Netomi
薪资未公开
工作地点India
地域资格限定地区(需当地身份)
时区要求日间重叠约 6 小时,基本正常作息
用工类型Full Time
发布时间14 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 India 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

关于公司:

Netomi 是企业客户体验领域的领先代理型 AI 平台。我们与 Delta 航空、MetLife、United 等全球知名品牌合作,通过整个客户旅程实现代理型自动化的大规模应用。我们的无代码平台提供最快的产品上市时间、最低的总体拥有成本,以及适用于任何 CX 用例的 AI 代理的简单、可扩展管理。Netomi 得到 WndrCo、Y Combinator 和 Index Ventures 的支持,帮助企业在效率、成本和客户体验质量方面取得提升。
想要成为人工智能革命的一部分,改变全球最大品牌做生意的方式吗?加入我们!

Netomi 正在寻找一位高度分析能力和注重细节的候选人加入古吉拉特邦的 Analytics 团队。作为团队的一员,你将与数据科学、产品、工程和客户成功团队合作,推动复杂的数据和趋势分析,提出改进方法,从而改善客户体验。你还将负责对各种产品运营项目进行基准测试和性能评估,构建并发布详细的评分卡和报告,基于客户和业务数据识别并推动新机会。

我们正在寻找一位热爱利用数据发现和解决现实问题的工程师。你将享受处理丰富的数据集,使用现代商业智能技术,并能够看到你的洞察力驱动客户的功能。你还将有机会与团队合作,参与制定政策、流程和工具,以应对产品质量问题。

职责:

  • 使用现代数据平台(如 Spark、Databricks、Airflow、Snowflake 等)架构和实现可扩展、安全、可靠的数据显示管道。
  • 开发 ETL/ELT 流程,从各种结构化和非结构化数据源中获取数据。
  • 进行探索性数据分析(EDA),发现趋势,验证数据完整性,并推导出指导数据产品开发和业务决策的洞察。
  • 与数据科学家、分析师和软件工程师紧密合作,设计支持高质量分析和实时洞察的数据模型。
  • 编写干净、可维护的代码,并编写全面的单元和集成测试,以确保 Python 中的可靠性与稳定性。
  • 在敏捷、协作的环境中茁壮成长,并对端到端的工作负责。
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About the Company:

Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.
Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!
Netomi is seeking a highly analytical and detail-oriented candidate to join the Analytics team in Gurugram. As part of the team, you will work with data science, product, engineering, and customer success teams to drive complex data and trend analyses to propose ways to improve and, thereby contributing to improve the experience. You will also be responsible for benchmarking and measuring the performance of various product operations projects, building and publishing detailed scorecards and reports, identifying and driving new opportunities based on customer and business data.

We are looking for an Engineer with a passion for using data to discover and solve real-world problems. You will enjoy working with rich data sets, modern business intelligence technology, and the ability to see your insights drive the features for our customers. You will also have the opportunity to contribute to the development of policies, processes, and tools to address product quality challenges in collaboration with teams.
Responsibilities:

  • Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake, etc.).
  • Develop ETL/ELT processes to ingest data from various structured and unstructured sources.
  • Perform Exploratory Data Analysis (EDA) to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions.
  • Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights.
  • Write clean, maintainable code with comprehensive unit and integration tests to ensure reliability and stability in Python.
  • Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 4+ years of hands-on experience in data engineering or backend software development roles.
  • Solid understanding of Relational Databases (RDS, MySQL, PostgreSQL).
  • Experience with Apache Kafka or RabbitMQ for building asynchronous, decoupled systems.
  • Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect).
  • Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks).
  • Deep understanding of data modeling, data warehousing, and distributed systems.

Additional Skills:

  • Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).
  • Exposure to AI/ML-integrated solutions or interest in working alongside data science teams.
  • Knowledge of data security and privacy regulations (e.g., GDPR, HIPAA).
  • Familiarity with prompt engineering and how LLM-based systems interact with data

Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
Originally posted on Himalayas

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