高级数据工程师
Senior Data Engineer
关于 Spokeo:
通过数据让世界更加透明。
Spokeo 是一个人员智能平台,帮助超过 1800 万的月活跃用户重新联系朋友、与家人团聚,并在新关系中建立信任。数以千计的公司也信赖 Spokeo 的 600 亿条公开记录,以改善客户研究、验证信息并防止欺诈。
Spokeo 自 2006 年成立以来,打造了一支专注的远程优先团队,平均任职时间为 6.9 年。它曾获得 Comparably 颁发的“最佳薪酬公司”、“员工幸福感”、“福利和待遇”、“对女性的支持”、“工作与生活平衡”以及“CEO 领导力”等荣誉。
关于这个职位
作为 Spokeo 的高级数据工程师,您将开发、优化和改进我们的数据系统,包括 ETL 流水线、存储和实体解析。这涉及使用 AWS 构建的基础设施,包括 Airflow、PySpark、EMR、S3、DynamoDB 等。该职位将帮助构建和改进数据产品、自动化平台功能、分析软件包和数据流水线编排工具。
您将负责:
- 构建基础设施和数据自动化流水线,从各种来源获取、处理和加载数据。将新的组件自动化并集成到数据流水线中。
- 与利益相关者和数据科学团队合作,开发数据产品,包括实体解析和最佳选择,以高效执行产品愿景和战略,与组织目标和优先事项保持一致。
- 创建单元测试和压力测试组件,监控技术性能并确保识别的问题得到解决。
- 开发数据分析工具,提供数据洞察并捕获关键指标。
- 研究解决方案并维护技术文档。
- 遵循数据治理、质量、清洗和其他 ETL 相关活动的最佳实践。
您需要具备:
- 要求:在生产环境中有 7 年以上数据工程开发经验(不包括实习和学术环境)。
- 具备处理超过 1 亿条记录或多个 TB 数据集的实际经验。
- 要求:在 AWS 上使用 EMR 有 5 年以上在高可扩展、分布式系统和集群架构中的开发经验。
- 要求:有 5 年以上 Python 编程的实战经验。
- 要求:有 5 年以上在大数据生态系统中的专业经验;必须熟悉 Spark;PySpark 为佳。
查看英文原文
About Spokeo:
Join our mission to make the world more transparent with data.
Spokeo is a people intelligence platform that helps over 18 million monthly visitors reconnect with friends, reunite with families, and build trust in new relationships. Thousands of companies also trust Spokeo’s 60 billion public records to improve customer research, help verify information, and prevent fraud.
Founded in 2006, Spokeo has built a dedicated, remote-first team with an average tenure of 6.9 years. It has earned recognition from Comparably as a Best Company for Compensation, Employee Happiness, Perks and Benefits, Support for Women, Work-Life Balance, and CEO Leadership.
About this Opportunity
As a Senior Data Engineer at Spokeo, you will develop, optimize, and improve our data systems, including ETL pipelines, storage, and entity resolution. This involves working with infrastructure built in AWS, including Airflow, PySpark, EMR, S3, DynamoDB, and more. This role will help build and improve data products, automation platform features, analytical software packages, and data pipeline orchestration tools.
What You’ll Do:
- Build infrastructure and data automation pipelines to ingest, process, and load data from various sources. Automate and integrate new components into the data pipeline.
- Collaborate with stakeholders and data science teams to develop data products, including entity resolution and best selection, to efficiently execute product vision and strategy in alignment with organizational goals and priorities.
- Create unit and stress-test components to monitor technical performance and ensure that identified issues are resolved.
- Develop data analysis tools to provide data insights and capture key metrics.
- Research solutions and maintain technical documentation.
- Follow best practices for data governance, quality, cleansing, and other ETL-related activities.
Who You Are:
- Required: 7+ years of development experience in data engineering within a production environment (internships and academic settings excluded).
- Proven experience working with large datasets exceeding 100M+ records or multiple terabytes.
- Required: 5+ years of development experience in highly scalable, distributed systems and cluster architectures using AWS and utilizing EMR.
- Required: 5+ years of hands-on programming experience with Python.
- Required: 5+ years of professional experience working in big data ecosystems; Spark is required; PySpark is preferable.
- Required: 5+ years of experience with SQL, schema design, and dimensional data modeling.
- Required: 5+ years of professional experience working with dataflow orchestration tools, such as Airflow.
- Required: 2+ years of experience with non-relational databases (e.g., DynamoDB, Elasticsearch, etc.).
- Required: A bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field is required.
Working at Spokeo
Spokeo offers a bonus program, equity plans, and a 401 (k). Once a year, we do a discretionary, merit-based salary increase. Additional benefits include 100% medical/dental/vision coverage and unlimited employee PTO.
Hiring at Spokeo
We extend written offers to candidates who successfully complete their selection process. Offers will depend on several factors, including, but not limited to, marketplace competition, job leveling, experience, and skills.
Privacy Notice for Candidates:
Spokeo is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status. Spokeo fosters a business culture where ideas and decisions from all people help us grow, innovate, create the best products, and be relevant in a rapidly changing world.
Recruiters or staffing agencies: Spokeo is not obligated to compensate any external recruiter or search firm who presents a candidate or their resume or profile to a Spokeo employee without 1) a current, fully executed agreement on file, and 2) being assigned to the open position (as a search) via our applicant tracking solution.
Use of Artificial Intelligence in Our Hiring Process
Spokeo may use artificial intelligence-enabled tools to support portions of the recruiting process. These tools may help our recruiting team organize, review, and summarize application materials, candidate experience, and interview information. They may also identify potential inconsistencies or verification signals in application materials for further human review.
AI-enabled tools assist our recruiting team but do not replace human judgment. Employment decisions are made by people based on a candidate’s qualifications and the role's requirements.
Originally posted on Himalayas