数据工程师负责人
Lead Data Engineer
Magna Legal Services 是一家值得信赖的全国性合作伙伴,为律师事务所、企业、保险公司和政府机构提供全面的法律支持,助力案件每个阶段的顺利进行。从法庭记录和档案检索到陪审团咨询、调查、诉讼图形和语言服务,我们帮助客户自信地应对复杂的法律挑战。我们的声誉建立在团队的专业知识、奉献精神和职业素养之上,我们自豪地营造一种文化,让有才华的人能够从事有意义的工作并实现职业成长。
Magna Legal Services 正在寻找一位实践型的高级数据工程师,为我们的企业数据平台的设计、开发和持续演进提供技术领导。该职位将负责可扩展的 ETL/ELT 流水线和 Snowflake 数据仓库的架构与优化,制定工程标准,并指导组织内可靠数据解决方案的交付。高级数据工程师将与技术和业务利益相关者合作,指导团队成员,并积极参与实施,以现代化和扩展我们的数据基础设施。
主要职责
- 负责 Snowflake 数据仓库的技术方向、架构及持续演进,对性能、可扩展性、安全性、可靠性及成本效率负责。
- 领导跨数据源和目标的可扩展 ETL/ELT 流水线的设计、开发和标准化工作,包括向 Azure Data Factory 的持续演进。
- 制定并维护代码质量、测试、文档、版本控制、部署、监控和数据质量方面的工程标准。
- 领导维度数据模型的设计和开发,包括使用 dbt、Sigma 和相关技术在分层架构中的星型模式。
- 与技术和业务利益相关者合作,将数据需求转化为优先级明确的技术路线图,并交付可信任、可重用的数据解决方案,以支持公司内部的决策。
- 通过方案设计和代码审查提供技术指导,指导数据工程师和分析师,帮助团队解决复杂的技术挑战。
- 评估并引入工具、模式和流程改进,以增强可扩展性、可靠性、可维护性和交付效率。
- 从需求开始领导复杂和临时的数据工程项目
查看英文原文
Magna Legal Services is a trusted nationwide partner to law firms, corporations, insurance carriers, and government agencies, delivering comprehensive legal support at every stage of a case. From court reporting and record retrieval to jury consulting, investigations, litigation graphics, and language services, we help our clients navigate complex legal challenges with confidence. Our reputation is built on the expertise, dedication, and professionalism of our team, and we’re proud to foster a culture where talented people can do meaningful work and grow their careers.
Magna Legal Services is seeking a hands-on Lead Data Engineer to provide technical leadership for the design, development, and ongoing evolution of our enterprise data platform. This role will own the architecture and optimization of scalable ETL/ELT pipelines and our Snowflake data warehouse, establish engineering standards, and guide the delivery of reliable data solutions across the organization. The Lead Data Engineer will partner with technical and business stakeholders, mentor team members, and remain actively involved in implementation as we modernize and scale our data infrastructure.
Primary Responsibilities
- Own the technical direction, architecture, and ongoing evolution of our Snowflake data warehouse, with accountability for performance, scalability, security, reliability, and cost efficiency.
- Lead the design, development, and standardization of scalable ETL/ELT pipelines across data sources and destinations, including the continued evolution toward Azure Data Factory.
- Establish and uphold engineering standards for code quality, testing, documentation, version control, deployment, monitoring, and data quality.
- Lead the design and development of dimensional data models, including star schemas within a medallion architecture, using tools such as dbt, Sigma, and related technologies.
- Partner with technical and business stakeholders to translate data needs into a prioritized technical roadmap and deliver trusted, reusable data solutions that support decision-making across the company.
- Provide technical guidance through solution design and code reviews, mentor data engineers and analysts, and help the team resolve complex technical challenges.
- Evaluate and introduce tools, patterns, and process improvements that strengthen scalability, reliability, maintainability, and delivery efficiency.
- Lead complex and ad hoc data engineering initiatives from requirements through delivery while promoting data governance, data literacy, and responsible data practices across the organization.
Desired Background
- Bachelor's degree in computer science, Information Technology, Engineering, or a related field.
- 5+ years of progressive experience in data engineering, including ownership of complex initiatives and technical leadership within a modern cloud data environment.
- Advanced hands-on experience with Snowflake, including data warehouse architecture, performance tuning, security and access controls, and cost optimization.
- Advanced SQL skills and strong experience with a scripting language such as Python for data processing, automation, and troubleshooting.
- Strong experience designing and operating scalable ETL/ELT pipelines, including orchestration, testing, monitoring, and production support.
- Hands-on experience with dimensional data modeling, star schema and medallion architectures, and dbt or a comparable transformation framework.
- Experience with Azure Data Factory or a comparable cloud orchestration platform; experience modernizing or migrating legacy data pipelines is preferred.
- Demonstrated technical leadership through mentoring, design and code reviews, engineering standards, and cross-functional delivery, with strong communication and prioritization skills.
Magna Legal Services provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Originally posted on Himalayas