数据工程师
Data Engineer
在一家真正相信自己所做之事的公司工作，是一件有趣的事情！
我们致力于将热情和客户关注带入业务中。
在 Cisive，我们的愿景是让找到合适人才变得轻松。我们提供以技术为核心的背景审查、身份验证和持续监控解决方案，帮助组织有信心地招聘和管理其员工队伍。
我们的价值观
- 诚信为先：我们在所有工作中坚持最高的道德标准。
- 勇于创新：我们挑战现状，拥抱新兴技术，并不断优化我们的解决方案，以满足行业需求。
- 共同成功：我们打破壁垒，分享知识，推动跨部门、品牌和全球办公室的团队合作，实现共同目标。
- 客户至上：我们超越交易性互动，成为风险缓解和员工管理方面的可信赖合作伙伴。
- 永远领先一步：我们主动寻求知识，帮助我们和客户始终走在趋势前面。
职位描述：
数据工程师（微软技术栈）
加入我们协作的数据与人工智能团队，每位成员的贡献都受到重视并可见。作为数据工程师，你将承担直接影响我们 Cisive 项目和业务的重要职责。这是一个绝佳的机会，适合希望亲手使用微软云原生数据技术、在现代数据平台开发新技能，并获得认可的人。你将得到经验丰富的专业人士的支持，并有机会在前沿的云环境中展示你的工作。
职责：
- 与数据和 AI 团队合作，设计和构建数据基础设施，包括使用 Azure Data Factory 的 ETL/ELT 流水线。
- 使用 Azure SQL Server 和 Azure SQL Database 开发和维护数据模型、云数据仓库和数据湖。
- 编写和优化 T-SQL 脚本、存储过程和函数，用于数据转换和集成。
- 支持数据质量、治理和安全计划。
- 参与数据项目的全生命周期，从需求收集到部署和监控。
资格要求：
- （必需）3 年以上数据工程经验，最好有微软数据技术经验。
- （必需）计算机科学、数据科学、信息系统或相关领域的学士学位。
- （必需）扎实的 SQL 技能和经验
查看英文原文
It's fun to work in a company where people truly BELIEVE in what they're doing!
We're committed to bringing passion and customer focus to the business.
At Cisive, our vision is to make securing the right talent effortless. We provide technology-first background screening, identity verification, and continuous monitoring solutions that help organizations hire and manage their workforce with confidence.
Our Values
- Integrity First: We uphold the highest ethical standards in everything we do.
- Innovate Fearlessly: We challenge the status quo, embrace emerging technologies, and continuously refine our solutions to stay ahead of industry needs.
- Win Together: We break down barriers, share knowledge, and champion teamwork across departments, brands, and global offices to achieve our collective goals.
- Customer Obsessed: We go beyond transactional interactions to become trusted partners in risk mitigation and workforce management.
- Stay One Step Ahead: We proactively seek knowledge that helps us—and our clients—stay ahead of the curve.
Job Description:
Data Engineer (Microsoft Stack)
Join our collaborative Data and AI team, where every member's contributions are valued and visible. As a Data Engineer, you'll take on meaningful responsibilities that directly impact our projects and business at Cisive. This is an excellent opportunity for someone eager to work hands-on with Microsoft's cloud-native data technologies, develop new skills in modern data platforms, and be recognized for their achievements. You'll be supported by experienced professionals and have opportunities to showcase your work in cutting-edge cloud environments.
Responsibilities:
- Collaborate with the Data and AI team to design and build data infrastructure, including ETL/ELT pipelines using Azure Data Factory.
- Develop and maintain data models, cloud data warehouses, and data lakes using Azure SQL Server, and Azure SQL Database
- Write and optimize T-SQL scripts, stored procedures, and functions for data transformation and integration.
- Support data quality, governance, and security initiatives.
- Participate in the full lifecycle of data projects, from requirements gathering to deployment and monitoring.
Qualifications:
- (Required) 3+ years of data engineering experience, preferably with Microsoft data technologies.
- (Required) Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
- (Required) Strong SQL skills and experience with Microsoft SQL Server.
- (Required) Proficiency in modern coding practices, including Visual Studio Code, Git, and test frameworks (unit testing, regression testing, etc.).
- (Required) Experience with Azure Data Factory, SSIS, and/or other Microsoft Azure data services.
- (Required) Experience designing and implementing star schema data models.
- (Nice to Have) Experience with Databricks and Python
- Excellent problem-solving skills, attention to detail, and strong communication skills.
- Ability to work effectively in a team environment and manage multiple tasks with minimal supervision.
What We Offer:
- Hands-on experience with real-world data engineering projects using Microsoft’s data stack.
- Mentorship and guidance from experienced data professionals.
- Opportunities to take on significant responsibilities and make a tangible impact.
- A collaborative and inclusive work environment.
- Flexible/remote work options.
Originally posted on Himalayas