Analytics Solution Architect | APAC-Based | Fully Remote | Japanese N1/N2
Indexed description
APAC-based Japanese-speaking professionals - this could be for you!
If you have JLPT N1/N2 + Business English, are based in Australia, Singapore or elsewhere in APAC, and are comfortable working with Japanese teams during Japan business hours, wed love to hear from you.
Work Location: Remote (Anywhere within APAC)
Japanese biligual Tech Professionals in APAC - Work with Japan without relocating!
Responsibilities
- Lead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks/ Fabric. The ideal candidate will have a deep understanding of big data technologies, data engineering, and cloud computing, with a strong focus on Azure Databricks along with Strong SQL.
- Design and implement solutions on Microsoft Fabric, including Fabric Pipeline, Lakehouse, Warehouse and Real-Time Analytics (EventHouse).
- Knowledge on Migrate existing workloads (e.g., Synapse, Databricks, Data Mart) into Fabric
- Work closely with business stakeholders and other IT teams to understand requirements and deliver effective solutions.
- Oversee the end-to-end implementation of data solutions, ensuring alignment with business requirements and best practices.
- Lead the development of data pipelines and ETL processes using Azure Databricks, PySpark, and other relevant tools.
- Integrate Azure Databricks with other Azure services (e.g., Azure Data Lake, Azure Synapse, Azure Data Factory) and on-premise systems.
- Provide technical leadership and mentorship to the data engineering team, fostering a culture of continuous learning and improvement.
- Ensure proper documentation of architecture, processes, and data flows, while ensuring compliance with security and governance standards.
- Ensure best practices are followed in terms of code quality, data security, and scalability.
- Stay updated with the latest developments in Databricks and associated technologies to drive innovation.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong problem-solving skills and a proactive approach to identifying and resolving issues.
- Leadership skills with the ability to manage and mentor a team of data engineers.
- Power BI for dashboarding and reporting.
- Microsoft Fabric for analytics and integration tasks.
- Spark Streaming for processing real-time data streams.
- Familiarity with Azure Resource Manager (ARM) templates for infrastructure as code (IaC) practices.
- Demonstrated expertise of 8+ years in developing data ingestion and transformation pipelines using Databricks/Synapse notebooks and Azure Data Factory.
- Solid understanding and hands-on experience with Delta tables, Delta Lake, and Azure Data Lake Storage Gen2.
- Experience in efficiently using Auto Loader and Delta Live tables for seamless data ingestion and transformation.
- Proficiency in building and optimizing query layers using Databricks SQL.
- Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end analytics solutions.
- Prior experience in developing, optimizing, and deploying Power BI reports.
- Familiarity with modern CI/CD practices, especially in the context of Databricks and cloud-native solutions.
- Strong experience with Azure Databricks, including cluster management, notebook development, and Delta Lake.
- Proficiency in big data technologies (e.g., Hadoop, Spark) and data processing frameworks (e.g., PySpark).
- Deep understanding of Azure services like Azure Data Lake, Azure Synapse, and Azure Data Factory.
- Experience with ETL/ELT processes, data warehousing, and building data lakes.
- Strong SQL skills and familiarity with NoSQL databases.
- Experience with CI/CD pipelines and version control systems like Git.
- Knowledge of cloud security best practices.
Hybrid role in Japan with global project exposure and strong career growth.
Salary Type : Annual Salary
Salary Min : ¥ 18000000
Salary Max : ¥ 24000000
Currency Type : JPY
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