亚马逊Analytics Specialist SA, GCR Data Specialist SA team

This role is one of the Solutions Architecture organization at AWS. This role provides a unique opportunity to lead innovations and transformational change with large Enterprise customers in their journey to cloud. The essential requirement includes experience of analytics area, especially in data warehouse and data lake technologies. Familiar with services and products related to data analysis, for example: Redshift, EMR, ElasticSearch, Flink, Spark, Hbase, Kafka, Kinesis, Trino, Hudi, Iceberg, etc.Experience with Data and AI projects and tool usage will be given priority.

1) Drive overall market and technical strategy as it relates to AWS Big Data & Analytics services. 2) Execute the strategic business development plan while working with key internal stakeholders (e.g. account teams, channel teams, service teams, support, etc.). 3) Identify specific prospects/partners to approach while communicating the specific value proposition for their business and use case. 4) Build and enable the related partner ecosystem for Greater China and fill the business development pipeline by engaging with prospects, partners, and key customers. 5) Help define the market segments, customer base, and industry verticals we target within Greater China and set a strategic business development plan for target markets and ensure it's in line with the strategic direction. 6) Work closely with the customer base to ensure they are successful using AWS web services, making sure they have the technical resources required. 7) Understand the technical requirements of our customers and work closely with the internal development teams to guide the direction of our product offerings. 8) Develop long-term strategic partnerships and handle a high volume of engagements and the fast pace of the cloud computing market 9) Experienced with account management (Enterprise, SMB and startup) and solution selling ability. 10) Relevant technical experience and industry knowledge will be very heplful. BI conversation is very business oriented thus enterprise industry (for example, retail, manufacturing etc..) experience is must have. A day in the life 1) Customer meetings to learn their business needs and pain points. 2) Understand product positioning in the market and in front of competitors. 3) design Go-to-Market strategy of the product and track the results with adjustment during execution. 4) Alignment with front-end teams (BD/SA) to scale the business. 5) collaborate with WW service teams to feedback with findings gained in the field to help product enhancement & iteration. 6) Partner Synergy as either sell to/with/through them.

-数据库质量保证策略设计 -基于数据库内核架构（如事务引擎、存储管理、并发控制等），设计覆盖功能、性能、稳定性、安全性和灾难恢复的综合性测试策略 -针对极端场景（如硬件故障、网络分区、超大规模数据压力）和大事务/高并发场景，构建破坏性测试和压力测试模型 -测试用例开发 -编写自动化测试脚本（如Python/Perl/Shell/C++），覆盖SQL语法、事务隔离级别、锁机制、备份恢复等核心功能 -自动化测试工具以及测试用例管理平台的开发和管理工作。 使用各种测试工具和技术，自动化测试，记录和分析测试结果，并跟踪和验证缺陷 -编写测试报告和文档： 清晰准确地记录测试过程、结果和分析，编写测试报告和相关文档 -设计复杂场景测试用例，例如：极端压力测试：模拟百万级并发事务、TB级数据量下的系统稳定性；破坏性测试：强制断电、磁盘I/O错误注入、内存溢出等异常场景；边界条件测试：验证索引深度、页分裂、日志写满等临界值场景 -性能分析与调优 -使用工具（如sysbench、tpcc、tpch、自定义基准测试）分析查询执行计划、锁竞争、I/O瓶颈 -结合内核日志（如InnoDB redo log、PostgreSQL WAL）定位性能问题，推动优化方案落地 -缺陷管理与协作 -搭建测试环境（含多节点集群、混合负载），复现并跟踪内核级Bug（如死锁、数据不一致） -与开发团队紧密合作，提供Root Cause Analysis（RCA）支持，参与代码审查，提供测试反馈，协助开发人员定位和修复问题，推动内核代码修复 -技术预研与创新 -探索新技术（如向量化查询、持久内存、分布式事务）的测试方法 -开发定制化测试工具（如混沌工程平台、自动化故障注入系统）

1. 营销策划与执行：负责平台站内营销活动/大促的策略输出、创意策划和落地执行，包括但不限于节日节点。根据目标用户群体、营销主题与市场需求，设计站内+站外创意活动方案，提升平台新客获取和老客留存，推动平台交易增长。 2. 跨部门协调与合作：与市场、产品等团队紧密合作，组织跨部门会议，推动活动进展与关键节点的按时落地。 3. 数据分析与优化：跟踪活动的效果，分析流量、转化、补贴等数据，及时优化营销策略。基于数据结果提出优化方案，确保活动持续提升平台效益。 4. 活动Communication：设计传播策略和传播节奏，通过站内渠道和站外媒体推广活动内容，确保物料符合主题氛围并激发用户参与兴趣。 1. Marketing Planning & Execution: Responsible for the strategy, creative planning, and execution of on-platform marketing activities and major promotions, including but not limited to holiday campaigns. Design on-platform and off-platform creative activity plans based on target user groups, marketing themes, and market demand to enhance user acquisition, retention, and drive platform transaction growth. 2. Cross-Department Coordination & Collaboration: Work closely with teams such as Marketing, Product, and others. Organize cross-department meetings to drive the progress of activities and ensure key milestones are met on time. 3. Data Analysis & Optimization: Track and analyze the effectiveness of campaigns, including metrics such as traffic, conversion, and subsidies. Continuously optimize marketing strategies based on data insights and propose improvement plans to ensure sustained platform benefits. 4. Campaign Communication: Design communication strategies and timing for campaign promotion through on-platform channels and external media. Ensure that marketing materials align with the campaign theme and generate user interest and participation.