The point where experts and best companies meet
Microsoft Senior Technology Consultant - Data & AI A2 Taiwan, Taoyuan City 948817337
02.09.2025
Share
Qualifications
- 10+ years of Data Engineering experience.
- Over 5 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata
- Strong Experience in large database solutions, on premises, cloud, and hybrid implementations
- Strong experience in Serverless Architecture/Microservices
- Strong experience of full application life cycle design tools and methodologies
- Strong experience in one or more technologies under each of the following
- Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight.
- Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture,
- Columnar (RedShift, Vertica)
- OSS (MySQL, PostgreSQL and MariaDB)
- CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores)
- Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations.
- Strong experience in Data Engineering:
- Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data
- Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza)
- Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform.
- Expertise in implementation of Data governance practices using either open source or proprietary tools.
- Expertise in Data Ops
- Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible.
- Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain.
- Good to have AI/ML experience:
- Experience in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps).
- Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search
- Good understanding of Prompt Engineering Basics
- Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes.
- Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models.
- Foundational Understanding of deep learning frameworks such as TensorFlow, PyTorch, LangChain/LangGraph and ONNX, with practical experience in NLP, computer vision, or time-series forecasting.
Responsibilities
- Works as a Individual contributor or Leads the engineering team and provides accurate time estimates, sets work priorities, and makes project changes and trade-offs necessary for a successful release.
- Applies technical experience and industry-specific knowledge to develop solutions, based on an analysis of how the proposed approach affects the business objectives of customers and partners.
- Works to accelerate the value proposition of customer or partner engagements by helping to design, develop, and deploy solutions, based on Microsoft technologies and methodologies.
- Applies information-compliance and assurance policies to ensure stakeholder confidence.
- Responsible for the overall efficacy and quality of a project team’s technical delivery within his or her engagements.
- Defines dependencies and risks that go beyond the immediate scope and timeframe for a complex project. Develops contingency plans, risk-mitigation implementation criteria, and alternative strategies to manage short- and long-term risks and manages technical escalations.
- Identifies a best practice approach for a project, across a wide scope of technical issues, and develops or reuses intellectual capital with customers, world-wide, and for programs and initiatives across Microsoft.
- Drives opportunities to expand or accelerate the adoption and consumption of the cloud and Microsoft technologies. Collaborates, as appropriate, with peers and other teams (e.g., Sales, account-aligned team) to scale the business with existing high-stake or strategic customers, by articulating/developing value propositions of strategic Microsoft products and services.
- Drives innovation and digital transformation. Ensures the use of the existing intellectual property (IP) and improves predictability.
- Defines the technology strategy for large and complex engagements, so that customers or partners realize the full value of investment. Responsible for implementing the technology strategy.
- Drives new ways of thinking, across the division and subsidiary, to improve quality, engineering productivity, and responsiveness to feedback and changing priorities.
These jobs might be a good fit
