← 返回岗位列表美国IT/互联网fulltime

数据工程师(Azure)- 远程,拉丁美洲

雇主

Bluelight Consulting

地点

远程 · 美国

待遇

$面议

工作模式

远程

截止日期

12月6日

🤖 AI 简历匹配评估

检测你的简历与该岗位的匹配度,免费

免费评估

岗位摘要

Bluelight is a leading software consultancy dedicated to designing and developing innovative technology that enhances users' lives.

岗位职责

Bluelight is a leading software consultancy dedicated to designing and developing innovative technology that enhances users' lives. With a steadfast commitment to delivering exceptional service to our clients, Bluelight excels in its focus on quality and customer satisfaction. Our mission is not only to create cutting-edge applications but also to foster a collaborative and enriching work environment where each team member can grow and thrive. With a presence across the United States and Central/South America, Bluelight is in an exciting phase of expansion, continually seeking exceptional talent to join its dynamic and diverse community.As an ETL Data Engineer, you will play a critical role in our client’s expanding data engineering team, designing, developing, and maintaining data integration processes primarily using Python (PySpark) and Azure Synapse Analytics to ensure the accuracy and availability of analytical data. Working closely with data scientists, analysts, and other stakeholders to deliver high-quality data for insights and decision-making, this position is ideal for a passionate software development professional who thrives in a fast-paced, dynamic environment where everyone's opinions and efforts are valued. By joining our client’s growing software consultancy, you will have the opportunity to contribute to challenging, market-standing projects within a collaborative community that deeply values hard work, continuous learning, personal growth, and professional development.Responsibilities
ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extractions, transformation, and loading.
Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool.
Data Source Expertise: Extract data from various sources, including REST APIs, SWL database tables, and CSV files.
Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance.
Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities.
Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements.
Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency.
Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs.
Monitoring and Troubleshooting: Monitoring ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability.
Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations.
Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives.
Security and Compliance: Ensure data security and compliance with data governance and privacy standards.
Qualifications
Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus.
Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault.
Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data.
Knowledge of data integration best practices and tools.
Experience with version control systems, such as Git (Azure DevOps).
Strong problem-solving and analytical skills, with a keen attention to detail.
Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities.
Familiarity with big data technologies, machine learning, and data analysis preferred.
Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus.
Being a consultant in our team is a fun, challenging, and rewarding career choice. Your contributions are highly valued by clients, and the work you do often has a direct and significant impact on their business.You will have the opportunity to work on a variety of projects for our incredible clients, which will accelerate your career growth. You’ll collaborate with modern technologies and work alongside some of the best professionals in the industry!If you’re eager to be part of an exciting, challenging, and rapidly growing consultancy, we encourage you to apply. Originally posted on Himalayas

申请条件

- 精通Python(PySpark)和Azure Synapse Analytics(Notebooks/Pipelines)
- 具备数据仓库专业知识,熟悉星型模式、事实表和维度表
- 有大规模并行处理(MPP)SQL池的设计与构建经验
- 能开发、维护ETL数据集成流程,确保数据准确性和可用性
- 能与数据科学家、分析师及利益相关者紧密协作
- 适应快节奏、动态的工作环境,重视团队合作和意见交流
- 具备软件开发和数据工程实践经验
- 对持续学习、个人成长和专业发展有强烈意愿

雇主简介

Bluelight Consulting is a software consultancy that designs and develops innovative technology solutions, with a focus on quality and customer satisfaction, operating across the United States and Central/South America.

对这个岗位感兴趣?

该岗位暂未开放在线申请,顾问可为您推荐同类岗位或申请指导

咨询不收取任何费用,顾问将为您推荐合适的岗位与申请方式

申请海外岗位,英文简历符合当地格式规范吗?

AI 自动评估你与该岗位的匹配度,3 分钟出结果

免费评估简历匹配度

数据来源:Himalayas

岗位信息来源于公开渠道,版权归原作者所有