Databricks 实践负责人
Databricks Practice Lead
我们正在寻找一位经验丰富的Databricks实践负责人，以推动Databricks实践的技术愿景、增长和交付卓越。该职位结合了现代数据工程的深入实战技能与领导职责，包括定义技术标准、指导工程团队、支持业务发展，并为客户提供可扩展的云基础数据解决方案。
你将与客户、工程团队、解决方案架构师、交付负责人和业务利益相关者紧密合作，设计创新的数据平台，指导技术决策，并扩展组织的Databricks能力。理想的候选人既是强大的技术领导者，也是值得信赖的顾问，能够将业务目标与现代数据工程解决方案相结合。
职责
- 领导Databricks实践的技术方向和增长，建立标准、最佳实践和可重用的解决方案加速器。
- 使用Databricks、Apache Spark和Microsoft Azure设计和审查企业级数据平台架构。
- 在多个客户项目中提供技术领导力和架构指导。
- 与客户合作，了解业务挑战并推荐可扩展的数据和分析解决方案。
- 领导与客户的技術探索会议、解决方案研讨会、架构评审和设计讨论。
- 指导和辅导数据工程师、技术负责人和解决方案架构师，促进技术卓越和职业发展。
- 定义数据工程、软件工程、DevOps、安全、治理和运营卓越的最佳实践。
- 建立ETL/ELT开发、数据质量、监控、性能优化和生产支持的标准。
- 推动现代数据架构的采用，包括Lakehouse、Delta Lake和事件驱动的数据处理。
- 与交付经理和工程经理合作，支持项目规划、人员配置、技术风险管理和解决方案质量。
- 支持售前活动，包括解决方案设计、技术提案、工作量估算、客户演示和概念验证项目。
- 跟踪Databricks平台功能和新兴技术，识别改进服务和扩展实践机会。
- 在实践中推广AI辅助软件开发和工程最佳实践。
查看英文原文
We are seeking an experienced Databricks Practice Lead to drive the technical vision, growth, and delivery excellence of our Databricks practice. This role combines deep hands-on expertise in modern data engineering with leadership responsibilities, including defining technical standards, mentoring engineering teams, supporting business development, and delivering scalable cloud-based data solutions for enterprise clients.
You will work closely with clients, engineering teams, solution architects, delivery leaders, and business stakeholders to design innovative data platforms, guide technical decision-making, and expand the organization's Databricks capabilities. The ideal candidate is both a strong technical leader and a trusted advisor who can bridge business objectives with modern data engineering solutions.
Responsibilities
- Lead the technical direction and growth of the Databricks Practice, establishing standards, best practices, and reusable solution accelerators.
- Design and review enterprise-scale data platform architectures using Databricks, Apache Spark, and Microsoft Azure.
- Provide technical leadership and architectural guidance across multiple client engagements.
- Partner with clients to understand business challenges and recommend scalable data and analytics solutions.
- Lead technical discovery sessions, solution workshops, architecture reviews, and design discussions with clients.
- Mentor and coach Data Engineers, Technical Leads, and Solution Architects, fostering technical excellence and career development.
- Define best practices for data engineering, software engineering, DevOps, security, governance, and operational excellence.
- Establish standards for ETL/ELT development, data quality, monitoring, performance optimization, and production support.
- Drive adoption of modern data architectures, including Lakehouse, Delta Lake, and event-driven data processing.
- Collaborate with Delivery Managers and Engineering Managers to support project planning, staffing, technical risk management, and solution quality.
- Support pre-sales activities, including solution design, technical proposals, effort estimation, client presentations, and proof-of-concept initiatives.
- Stay current with Databricks platform capabilities and emerging technologies, identifying opportunities to improve services and expand practice offerings.
- Promote the adoption of AI-assisted software development and engineering best practices across the practice.
- 8+ years of professional experience in Data Engineering, Data Platform Engineering, or related disciplines.
- 3+ years of experience leading technical teams, architecture initiatives, or data engineering practices.
- Deep expertise with Databricks, including workspace administration, notebooks, jobs, workflows, Unity Catalog, Delta Lake, and Lakehouse architecture.
- Strong experience developing scalable data pipelines using Apache Spark (PySpark).
- Extensive experience with Microsoft Azure, including services such as Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Event Hubs, Azure Key Vault, and Azure DevOps.
- Strong programming skills in Python, including clean coding practices and object-oriented programming principles.
- Experience with orchestration tools such as Apache Airflow or Dagster.
- Experience working with streaming technologies such as Apache Kafka or Azure Event Hubs.
- Strong understanding of data architecture, dimensional data modeling, metadata management, and enterprise data platform design.
- Experience implementing data governance, data quality, security, and compliance practices.
- Experience building and optimizing enterprise ETL/ELT solutions.
- Strong knowledge of SQL and relational database concepts.
- Experience deploying cloud-native data solutions, preferably on Microsoft Azure.
- Excellent consulting, presentation, and stakeholder management skills with experience interacting directly with enterprise clients.
- Experience leading architecture discussions, technical governance, and solution reviews.
- Ability to lead multiple initiatives simultaneously while providing technical direction across distributed teams.
- Experience working in Agile development environments.
Perks you enjoy at KMSMexico
- Mexican law benefits
- 15 days of PTO (in year zero, from the first year onwards it is 3 days per year).
- 5 days' leave for the death of immediate family members, negotiable.
- Major Medical Expenses Insurance with coverage for immediate dependents (spouse and children).
- Annual performance bonus (≈10% of annualized salary).
- Annual salary adjustment.
- Employee Referral Bonus.
- Paid Certifications / Courses
- Coursera License.
- 5% Savings Fund.
- 5% Grocery Vouchers.
At KMS Technology Mexico, we are passionate about building innovative software solutions that drive impact. As part of an international tech company, we offer a collaborative and inclusive environment where your ideas matter and your growth is our priority.
Originally posted on Himalayas