出海雷达

Databricks迁移工程师

Databricks Migration Engineer

开发工程限定地区(需当地身份)
公司Tier One Technologies
薪资未公开
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Other
发布时间12 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

简介
请注意:不接受公司对公司的候选人。

  • Tier One Technologies 正在寻找一名 Databricks 迁移工程师,以支持我们的美国政府客户。
  • 该远程合同转正职位将起源于弗吉尼亚州罗斯林。优先考虑东海岸时区的候选人。
  • 必须是美国公民。
  • 未获得必要许可的选定候选人将需要进行联邦政府背景调查以获得许可。

职责

  • 领导从传统的 SQL Server 存储过程和 ADF 管道到 Databricks Lakehouse(Delta Lake)的技术迁移,确保遵循最佳实践的 Lakehouse 设计。
  • 将传统的关系型数据仓库范式转化为可扩展、分布式 Lakehouse 框架(青铜层、银层、金层)。
  • 使用 PySpark、Delta Live Tables(DLT)和 Databricks Workflows 设计强大且可重用的 ETL/ELT 框架。
  • 架构并优化金层(维度模型、星型模式),以最大化 Power BI 的性能。
  • 优化 Databricks SQL 数据仓库,以支持高并发、低延迟的 Power BI 查询(DirectQuery 和 Import 模式)。
  • 实施高级优化技术,包括 Z-Ordering、数据跳过、液态聚类和物化视图。
  • 定义并执行集群大小、自动扩展策略和无服务器 SQL 计算的治理标准,以平衡性能与成本。
  • 实施主动监控仪表板,跟踪 Databricks 单位(DBU)消耗情况,并识别节省成本的机会。
  • 建立 Delta Lake 内部的分区策略和文件大小管理的最佳实践。
  • 使用 Unity Catalog 设计并实现强大的数据安全模型,用于集中治理。
  • 强制执行行级和列级安全策略,以确保 Power BI 用户和内部分析师的数据访问合规性。
  • 将 Lakehouse 安全架构与现有的企业 Azure Active Directory(Microsoft Entra ID)和 RBAC 标准保持一致。
  • 作为主要技术负责人,开展专门的配对编程会话、研讨会和代码审查,帮助团队从以 SQL 为中心转向以 Spark 为中心的思维方式。
  • 创建全面的技术文档,包括架构图、设计模式和优化手册。
  • 建立基础的知识转移框架,确保迁移后内部团队能够完全自给自足。
  • 能够有效地进行口头和书面沟通,与技术人员和非技术人员交流。
查看英文原文

Overview
PLEASE NOTE: No corp-to-corp candidates will be accepted.

  • Tier One Technologies is seeking a Databricks Migration Engineer to support our US Government client.
  • This remote Contract-to-Hire position will be originated in Rosslyn, VA. East Coast time zone candidates preferred.
  • Must be a US Citizen.
  • SELECTED CANDIDATES WITHOUT REQUIRED CLEARANCE WILL BE SUBJECT TO A FEDERAL GOVERNMENT BACKGROUND INVESTIGATION TO RECEIVE IT.

Responsibilities

  • Lead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design.
  • Translate traditional relational data warehousing paradigms into scalable, distributed Lakehouse frameworks (Bronze, Silver, Gold).
  • Design robust, reusable ETL/ELT frameworks using PySpark, Delta Live Tables (DLT), and Databricks Workflows.
  • Architect and refine the Gold Layer (dimensional models, star schemas) specifically to maximize Power BI performance.
  • Optimize Databricks SQL Warehouses to support high-concurrency, low-latency Power BI queries (DirectQuery and Import modes).
  • Implement advanced optimization techniques, including Z-Ordering, data skipping, liquid clustering, and materialized views.
  • Define and enforce governance standards for cluster sizing, auto-scaling policies, and serverless SQL compute to balance performance with cost.
  • Implement proactive monitoring dashboards to track Databricks Unit (DBU) consumption and identify cost-saving opportunities.
  • Establish best practices for partition strategies and file size management within Delta Lake.
  • Design and implement a robust data security model using Unity Catalog for centralized governance.
  • Enforce row-level and column-level security policies to ensure compliant data access for Power BI consumers and internal analysts.
  • Align the Lakehouse security architecture with existing enterprise Azure Active Directory (Microsoft Entra ID) and RBAC standards.
  • Act as the primary technical lead, conducting dedicated pair-programming sessions, workshops, and code reviews to transition the team from SQL-centric to Spark-centric thinking.
  • Create comprehensive technical documentation, including architecture diagrams, design patterns, and optimization playbooks.
  • Build a foundational knowledge transfer framework to ensure the internal team is fully self-sufficient post-migration.
  • Communicate effectively verbally and in written form to both technical and non-technical audience
  • Work in an organized fashion, completing tasks timely while paying close attention to details

Qualifications

  • Bachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in Data Engineering, Data System Development or related roles.
  • 5+ years of experience with Cloud platforms (e.g. Azure, AWS, GCP).
  • 1+ year leading complex, cross-functional data projects and technical teams.
  • Experience with Databricks Lakehouse, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms.
  • Experience with data warehousing, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark.
  • Excellent communication skills.
  • Must be a US Citizen and be able to obtain a Position of Public Trust Clearance.
  • Must have resided in the US for the last 5 years and not have traveled outside the US for a combined total of 6 months or more in last 5 years.

Originally posted on Himalayas

本页面信息整理自 Himalayas,版权归原发布方所有。职位可能随时关闭,投递请以原始页面为准。 本站只做信息聚合展示,不参与招聘流程,也不向求职者收取任何费用。

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