数据工程师 - Snowflake
Data Engineer - Snowflake
Tiger Analytics 是一家快速发展的高级分析咨询公司。我们的顾问在数据科学、机器学习和人工智能领域拥有深厚的专业知识。我们是多家财富 500 强公司的可信赖分析合作伙伴，帮助他们从数据中创造商业价值。我们的商业价值和领导力已获得包括 Forrester 和 Gartner 在内的多家市场研究机构的认可。随着我们继续打造全球最佳的分析咨询团队，我们正在寻找顶尖人才。
数据工程师将负责构建、设计和实现先进的分析能力。合适的候选人应具备数据库设计方面的广泛技能，能够处理大规模和复杂的数据集，有构建自助仪表板的经验，熟悉使用可视化工具，并能运用技能生成有助于解决业务挑战的洞察。我们希望找到一位能带来自己愿景并推动公司数据分析迈向新高度的积极变革者。
要求
- 12 年以上行业经验，特别是在数据工程领域，重点在 AWS 云技术栈和 AI 方面。
- 8 年以上在生产环境中构建和部署大规模数据处理管道的经验。
- 精通 Python、SQL 和 PySpark。
- 使用 Python 创建和优化复杂的数据处理和数据转换管道。
- 熟练掌握 SQL，有使用关系型数据库的经验，能够编写查询（SQL），并对多种数据库有基本了解。
- 在 AWS 上有 Snowflake/Databricks、dbt 以及 Apache Spark 等分布式计算框架的深入经验。
- 了解数据仓库（DWH）系统，以及从 DWH 迁移到数据湖/Snowflake 的经验。
- 了解 ELT 和 ETL 模式及其适用场景，了解数据模型并能将数据转换为模型。
- 具备处理非结构化数据集的分析能力。
- 构建支持数据转换、数据结构、元数据、依赖关系和工作负载管理的流程。
- 有在动态环境中支持和与跨职能团队合作的经验。
- 福利
- 随着公司的发展，有显著的职业发展机会。该职位提供一个独特的机会，加入一个小型、具有挑战性和创业精神的环境，拥有高度的个人责任感。
查看英文原文
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.
Requirements
- 12+ years of overall industry experience specifically in data engineering with a heavy focus on the AWS Cloud stack and AI.
- 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
- Advanced proficiency in Python, SQL, and PySpark.
- Creating and optimizing complex data processing and data transformation pipelines using python
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Deep experience with Snowflake/Databricks on AWS, dbt, and distributed computing frameworks like Apache Spark.
- Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
- Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Originally posted on Himalayas