数据工程师II
Data Engineer II
NPS Prism
职位：数据工程师
招聘地点：印度古吉拉特（远程办公）
经验：3–6年
雇佣类型：全职
公司简介：
NPS Prism 是由 Bain & Company 拥有的市场领先的基于云的客户体验基准和运营改进平台。NPS Prism 为客户提供可操作的洞察和分析，指导打造改变游戏规则的客户体验。基于坚实的抽样、研究和分析方法论，它让客户能够看到自己在整体 NPS® 以及客户旅程每个步骤上与竞争对手的对比情况。
通过 NPS Prism，您可以了解自己的优势所在、薄弱环节以及客户对与您及竞争对手做生意的感受，直接使用客户的原话。结果是：优先处理最重要的客户互动。NPS Prism 的客户利用我们的客户体验基准和洞察来推动增长并超越竞争对手。
NPS Prism 于 2019 年推出，迅速发展成为一支超过 200 人的团队，服务全球数十家客户。NPS Prism 完全由 Bain & Company 拥有，该公司是世界顶级管理咨询公司之一，常年被评为全球最佳工作场所之一。我们相信多样性、包容性和协作是打造卓越团队的关键。我们招募具有卓越才能、能力和潜力的人才，并创造一个让您成为最好的自己并在职业和个人生活中茁壮成长的环境。
职位概述：
我们正在寻找一位技能娴熟且经验丰富的数据工程师加入我们的团队。理想的候选人应具备 Python、SQL 和 PySpark 的专业知识，有在 Databricks 及 Azure 和 AWS 等云平台上的实际工作经验。对 ETL 工具如 Python 的扎实理解以及对 DevOps 实践和 CI/CD 流水线的基本知识将是一个优势。这是一个在动态且快节奏环境中工作的独特机会，负责设计和实现满足可扩展业务需求的稳健数据解决方案。需要使用 Git 和版本控制。
主要职责：
数据管道开发：
- 使用 Databricks、SQL、Python/pyspark 以及 Alteryx（有相关经验更佳）等工具设计、构建和优化 ETL/ELT 流程。
- 开发和维护稳健、可扩展且高效的数据显示管道，用于处理从源数据到新兴数据的大规模数据集。
云数据工程：
- 在 Azure、AWS 等云平台上开展工作，构建数据仓库、数据湖和其他云原生数据架构。
查看英文原文
NPS Prism
Title: Data Engineer
Hiring Location: Gurugram, India (Work From Home Role)
Experience: 3–6 Years
Employment Type: Full-time
Company Profile:
NPS Prism is a market-leading, cloud-based CX benchmarking and operational improvement platform owned by Bain & Company. NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences. Based on rock-solid sampling, research, and analytic methodology, it lets customers see how they compare to their competitors on overall NPS®, and on every step of the customer journey.
With NPS Prism you can see where you’re strong, where you lag, and how customers feel about doing business with you and your competitors, in their own words. The result: Prioritize the customer interactions that matter most. NPS Prism customers use our customer experience benchmarks and insights to propel their growth and outpace the competition.
Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world. NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a company consistently recognized as one of the world’s best places to work. We believe that diversity, inclusion, and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally.
Position Summary:
We are seeking a highly skilled and experienced Data Engineer to join our team. The ideal candidate will have strong expertise in Python, SQL and PySpark, with proven experience working on Databricks and cloud platforms such as Azure and AWS. A solid understanding of ETL tools like Python as well as basic knowledge of DevOps practices and CI/CD pipelines, will be advantageous. This is a unique opportunity to work in a dynamic and fast-paced environment to design and implement robust data solutions for scalable business needs. Working with Git and versioning.
Key Responsibilities:
Data Pipeline Development:
- Design, build, and optimize ETL/ELT workflows using tools like Databricks, SQL, Python/pyspark & Alteryx (Good to have).
- Develop and maintain robust, scalable, and efficient data pipelines for processing large datasets. from source to emerging data.
Cloud Data Engineering:
- Work on cloud platforms (Azure, AWS) to build and manage data lakes, data warehouses, and scalable data architectures.
- Utilize cloud services like Azure Data Factory, AWS Glue, or for data processing and orchestration.
Databricks and Big Data Solutions:
- Use Databricks for big data processing, analytics, and real-time data processing.
- Leverage Apache Spark for distributed computing and handling complex data transformations.
Data Management:
- Create and manage SQL-based data solutions, ensuring high availability, scalability, and performance.
- Develop and enforce data quality checks and validation mechanisms.
Collaboration and Stakeholder Engagement:
- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver impactful data solutions.
- Understand business requirements and translate them into technical solutions.
DevOps and CI/CD:
- Leverage CI/CD pipelines to streamline development, testing, and deployment of data engineering workflows.
- Work with DevOps tools like Git, Jenkins, or Azure DevOps for version control and automation.
Documentation and Optimization:
- Maintain clear documentation for data workflows, pipelines, and processes.
- Optimize data systems for performance, scalability, and cost-efficiency
Required Qualifications, Experience and Skills
Educational Qualifications:
· Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
Experience:
· 3–6 years of experience in Data Engineering or related roles.
- Hands-on experience with big data processing frameworks, data lakes, and cloud-native services.
Skills:
Core Skills:
- Proficiency in Python, SQL, and PySpark for data processing and manipulation.
- Proven experience in Databricks and Apache Spark.
- Expertise in working with cloud platforms like Azure, AWS.
- Sound knowledge of ETL processes and tools like Alteryx. (Good to have)
Data Engineering Expertise:
- Leveraging data lakes, data warehouses, and data pipelines.
- Data Pipeline – Build a Data Pipeline from scratch
- Strong understanding of distributed systems and big data technologies.
DevOps and CI/CD:
· Basic understanding of DevOps principles and familiarity with CI/CD pipelines.
- Hands-on experience with tools like Git, Jenkins, or Azure DevOps.
Preferred Qualifications:
· Familiarity with data visualization tools like Power BI, Tableau, or similar is a plus.
- Knowledge of streaming technologies such as Kafka or Event Hubs is desirable.
- Strong problem-solving skills and a knack for optimizing data solutions.
- Excellent communication (oral and written) skills
Originally posted on Himalayas