数据工程师
Data Engineer
关于 Urban SDK
Urban SDK 正在塑造智慧城市未来。我们是地理空间 AI 技术的先驱，为公共领导者提供关键决策的洞察和自动化工具。我们为关键公共服务配备地理空间 AI，使精准、数据驱动的决策更加高效和可靠。
我们对人才的承诺
我们致力于将业务增长与每位员工的职业成果相结合。我们的承诺得到了杰克逊维尔商业杂志和 Will Reed 的认可，被评为最佳工作场所之一。
关于该职位
我们正在寻找一位经验丰富的数据工程师，负责设计、构建和维护支持我们地理空间交通分析应用的可扩展数据管道和平台。理想的候选人应具备 Python、Databricks、S3 和现代数据工程实践（包括自动化测试、CI/CD 和数据质量监控）的经验。
职责
- 在 Databricks 和云平台上设计、实现并维护可扩展的数据管道和 ETL/ELT 工作流。
- 管理存储在 AWS S3 中的大规模地理空间和时间数据集。
- 与数据科学家合作，将机器学习模型部署到生产环境，并确保数据的顺畅可用性。
- 实现数据验证、测试和监控框架，以确保数据的准确性、一致性和可靠性。
- 优化数据存储和处理策略，以高效处理大量交通和移动数据。
- 编写和维护数据工作流、架构和流程的文档。
- 与跨职能团队紧密合作，了解数据需求并确保及时交付。
- 跟踪数据工程、云技术和大数据处理领域的最新趋势和最佳实践。
资格要求
- 计算机科学、数据工程或相关领域的学士或硕士学位。
- 3 年以上数据工程师或类似岗位的工作经验。
- 精通 Python 及其数据工程相关库（如 pandas、PySpark 等）。
- 具有 Databricks 和 Spark 处理大规模数据的实际经验。
- 具有 AWS 服务经验，尤其是 S3，并了解基于云的数据架构。
- 对数据管道测试、版本控制和 CI/CD 实践有扎实的理解。
- 具有 SQL 和 NoSQL 数据库的经验。
- 强大的问题解决能力和细致入微的注意力。
优先考虑的技能
- 熟悉地理空间数据格式和
查看英文原文
About Urban SDK
Urban SDK is shaping the Future of Smart Cities. We are pioneers in geospatial AI technology, providing public leaders with insights and automation for mission-critical decisions. We equip critical public services with geospatial AI, enabling precise, data-driven decisions with efficiency and confidence.
Our Commitment to People
We are committed to aligning business growth with professional outcomes for every employee. Our commitment has been recognized by Jacksonville Business Journal and Will Reed as a noted Best Places to Work.
About the role
We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and platforms that support our geospatial traffic analytics applications. The ideal candidate will have experience with Python, Databricks, S3, and modern data engineering practices, including automated testing, CI/CD, and data quality monitoring.
Responsibilities
- Design, implement, and maintain scalable data pipelines and ETL/ELT workflows on Databricks and cloud platforms.
- Manage large-scale geospatial and temporal datasets stored in AWS S3.
- Collaborate with data scientists to productionize machine learning models and ensure smooth data availability.
- Implement data validation, testing, and monitoring frameworks to ensure data accuracy, consistency, and reliability.
- Optimize data storage and processing strategies to handle high volumes of traffic and mobility data efficiently.
- Develop and maintain documentation for data workflows, architecture, and processes.
- Work closely with cross-functional teams to understand data requirements and ensure timely delivery.
- Stay up-to-date with the latest trends and best practices in data engineering, cloud technologies, and big data processing.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
- 3+ years of experience as a data engineer or in a similar role.
- Strong proficiency in Python and associated libraries for data engineering (pandas, PySpark, etc.).
- Hands-on experience with Databricks and Spark for large-scale data processing.
- Experience with AWS services, especially S3, and knowledge of cloud-based data architectures.
- Solid understanding of data pipeline testing, version control, and CI/CD practices.
- Experience with SQL and NoSQL databases.
- Strong problem-solving skills and attention to detail.
Preferred Skills
- Familiarity with geospatial data formats and processing (GeoJSON, Shapefiles, PostGIS).
- Experience with workflow orchestration tools (Databricks, Prefect, or similar).
- Knowledge of containerization (Docker/Kubernetes) and cloud-native data solutions.
- Experience supporting machine learning pipelines in production.
Compensation
- Location: Jacksonville, FL (Town Center Area) or Remote
- Type: Full-time
- Reports to: Director of Engineering
- Salary Based on Experience
- Annual Bonus
- Medical, Vision, Dental, 401(k)
- 21 Days Vacation
- Office Lunch provided Daily
Originally posted on Himalayas