Design and implement end-to-end data solutions on Microsoft Azure, including data lakes, data warehouses, and ETL/ELT processes.
Develop scalable and efficient data architectures that support large-scale data processing and analytics workloads.
Ensure high performance, security, and compliance within Azure data solutions.
Know various techniques (lakehouse, warehouse) and have experience implementing them.
Evaluate and choose appropriate Azure services such as Azure SQL Database, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks (configuring, costing, etc), Unity Catalog, and Azure Data Factory. Should have deep knowledge and hands-on experience with these Azure Data Services.
Ideally, knowledgeable and experienced with Microsoft Fabric.
Work closely with business and technical teams to understand and translate data needs into robust, scalable data architecture solutions.
Experience with data governance, data privacy, and compliance requirements.
Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
Provide expertise and leadership to the development team implementing data engineering solutions.
Collaborate with Data Scientists, Analysts, and other stakeholders to ensure data architectures align with business goals and data analysis requirements.
Optimize cloud-based data infrastructure for performance, cost-effectiveness, and scalability.
Analyze data workloads and recommend optimizations for performance tuning, cost management, and reducing complexity.
Monitor and address any issues related to performance and availability in cloud-based data solutions.
Experience in programming languages (e.g., SQL, Python, Scala). Hands-on experience using MS SQL Server, Oracle, or similar RDBMS platform.
Experience in Azure DevOps, CI/CD pipeline development
Hands-on experience working at a high level in architecture, data science, or combination.
In-depth understanding of database structure principles
Distributed Data Processing of big data batch or streaming pipelines.
Familiarity with data visualization tools (e.g., Power BI, Tableau, etc.)
Data Modeling and strong analytics skills. The candidate must be able to take OLTP data structures and convert them into Star Schema. Ideally, the candidate should have DBT experience along with data modeling experience.
Problem-solving attitude, Highly selfmotivated, selfdirected, and attentive to detail, Ability to prioritize and execute tasks effectively.
Attitude and aptitude are highly important at Hitachi; we are a very collaborative group.

We would like to see a blend of the following skills. Not all of these are required, however, Databricks and Spark are highly desirable:

Azure SQL Data Warehouse
Azure Data Factory
Azure Data Lake
Azure Analysis Services
Databricks/Spark
Python or Scala (Python preferred)
Data Modeling
Power BI
Database migration from legacy systems to new solutions
Design conceptual, logical and physical data models using tools like ER Studio, Erwin

Azure Data Architect