高级 Azure 数据工程师
Azure Senior Data Engineer
职位描述：
在Argano，高级数据工程师负责使用Microsoft Fabric和Azure数据平台实施现代数据工程解决方案。与数据架构师紧密合作，他们提供技术专长，并帮助将业务和技术需求转化为可扩展、安全且可靠的数据解决方案。该职位负责构建和维护数据管道、集成流程和分析就绪的数据平台，同时确保数据质量、性能和治理。高级数据工程师与数据架构师、软件开发人员、数据分析师和业务利益相关者协作，以成功推进数据项目，并确保在客户项目中持续提供一致且可靠的数据，同时不断改进Argano的数据工程能力和最佳实践。
职责：
- 开发、部署和维护从多个来源进行数据摄取、转换和集成的数据管道和工作流。
- 在Microsoft Fabric内构建和优化Lakehouse、Warehouse和分析解决方案。
- 使用SQL、Python和PySpark开发数据转换流程，以支持报告、分析和AI项目。
- 遵循Microsoft和行业最佳实践，确保数据质量、性能、安全性和治理。
- 与架构师、开发人员、分析师和业务利益相关者协作，交付数据驱动的解决方案。
- 参与使用Azure DevOps和Git进行开发、部署和协作的敏捷/Scrum团队。
- 记录数据解决方案，并紧跟Microsoft Fabric、Azure和现代数据工程技术的发展。
最低和/或优先资格：
教育：
- 信息科技、计算机科学或相关技术领域的学士学位。
经验：
- 5年以上数据工程的实际工作经验。
- 5年以上在Microsoft Azure数据平台内设计和实施解决方案的经验。
- 熟练掌握Microsoft Fabric，包括Lakehouse、Warehouse、Data Factory、Data Engineering和实时分析。
- 熟练使用Azure SQL数据库、SQL Server、T-SQL、Synapse Analytics和Fabric数据解决方案。
- 精通Python、PySpark和SQL。
- 具有设计和实施现代数据仓库、数据集市和企业级数据平台的经验。
- 具有构建和编排用于分析和操作的ETL/ELT管道的经验。
查看英文原文
JOB SUMMARY:
A Senior Data Engineer at Argano leads the implementation of modern data engineering solutions using Microsoft Fabric and the Azure data platform. Working closely with Data Architects, they provide technical expertise and help translate business and technical requirements into scalable, secure, and reliable data solutions. This role is responsible for building and maintaining data pipelines, integration processes, and analytics-ready data platforms while ensuring data quality, performance, and governance. The Senior Data Engineer collaborates with Data Architects, Software Developers, Data Analysts, and business stakeholders to deliver successful data initiatives and ensure consistent, reliable data delivery across client engagements while continuously improving Argano's data engineering capabilities and best practices.
RESPONSIBILITIES:
- Develop, deploy, and maintain data pipelines and workflows for data ingestion, transformation, and integration from multiple sources.
- Build and optimize Lakehouse, Warehouse, and analytics solutions within Microsoft Fabric.
- Develop data transformation processes using SQL, Python, and PySpark to support reporting, analytics, and AI initiatives.
- Ensure data quality, performance, security, and governance following Microsoft and industry best practices.
- Collaborate with architects, developers, analysts, and business stakeholders to deliver data-driven solutions.
- Participate in Agile/Scrum teams using Azure DevOps and Git for development, deployment, and collaboration.
- Document data solutions and stay current with Microsoft Fabric, Azure, and modern data engineering technologies.
MINIMUM AND/OR PREFERRED QUALIFICATIONS:
EDUCATION:
- A bachelor's degree in information technology, Computer Science or or a related technical field.
EXPERIENCE:
- 5+ years of hands-on experience in Data Engineering.
- 5+ years of experience designing and implementing solutions within the Microsoft Azure Data Platform.
- Strong experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Factory, Data Engineering, and Real-Time Analytics.
- Strong experience with Azure SQL Database, SQL Server, T-SQL, Synapse Analytics, and Fabric data solutions.
- Advanced proficiency in Python, PySpark, and SQL.
- Experience designing and implementing modern data warehouses, data marts, and enterprise-scale data platforms.
- Experience building and orchestrating ETL/ELT pipelines for analytical and operational workloads.
- Experience with data modeling techniques including dimensional modeling and star schema design.
- Experience with Git, Azure DevOps, CI/CD pipelines, and Infrastructure as Code concepts.
- Strong understanding of cloud security, governance, and data management best practices.
- Experience working within Agile/Scrum teams.
- Demonstrated ability to lead technical discussions and mentor junior team members.
CERTIFICATES, LICENSES, REGISTRATIONS:
- Microsoft Certified: Fabric Data Engineer Associate (DP-700).
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) (preferred).
- Databricks Certified Data Engineer Associate (Nice to Have).
- Databricks Certified Data Engineer Professional (Nice to Have).
SKILL REQUIREMENTS:
- Problem-Solving: Advanced problem-solving and analytical skills.
- Communication: Strong communication skills to convey technical concepts to non-technical stakeholders.
- Collaboration: Effective collaboration with cross-functional teams.
- Technical Consulting: Ability to provide technical expertise, recommend solution approaches, and guide implementation decisions to achieve successful project outcomes.
- Proactivity: Proactively identifies technical risks, data quality issues, performance bottlenecks, and opportunities for improvement, driving resolutions with minimal supervision.
- Adaptability: Passion for continuous learning and adopting emerging cloud, data, analytics, and AI technologies.
- Data Architecture: Expertise in data architecture and design principles.
- Database Knowledge: Advanced knowledge of relational and non-relational databases.
- Data Modeling: Strong understanding of dimensional modeling, data warehousing concepts, and analytics-focused design patterns.
- Programming Mastery: Proficiency in in SQL, Python, and PySpark.
- Optimization: Experience optimizing Spark workloads, SQL performance, storage architectures, and large-scale data pipelines.
Originally posted on Himalayas