Technical Architect - SME - Analytics at NEXUS CORPORATION

Tokyo, Tokyo, Japan -

Full Time

Start Date

Immediate

Expiry Date

07 Jun, 26

Salary

0.0

Posted On

09 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Databricks, Azure Fabric, Big Data, Data Engineering, Cloud Computing, SQL, PySpark, Azure Data Lake, Azure Synapse, Azure Data Factory, ETL/ELT, Delta Lake, CI/CD, Git, Data Governance, Mentorship

Industry

Staffing and Recruiting

Description

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. 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. Essential Skills: 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. Soft Skills: 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. Nice to have Skills: Power BI for dash boarding 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. Experience: 1. Demonstrated expertise of 8+ years in developing data ingestion and transformation pipelines using Databricks/Synapse notebooks and Azure Data Factory. 2. Solid understanding and hands-on experience with Delta tables, Delta Lake, and Azure Data Lake Storage Gen2. 3. Experience in efficiently using Auto Loader and Delta Live tables for seamless data ingestion and transformation. 4. Proficiency in building and optimizing query layers using Databricks SQL. 5. Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end analytics solutions. 6. Prior experience in developing, optimizing, and deploying Power BI reports. 7. Familiarity with modern CI/CD practices, especially in the context of Databricks and cloud-native solutions

Responsibilities

Lead the architecture, design, and implementation of advanced analytics solutions primarily using Azure Databricks/Fabric, focusing on developing robust data pipelines and ETL processes. Oversee end-to-end solution implementation while providing technical leadership and ensuring adherence to best practices in code quality, security, and scalability.