Cloud Data Architect

Skills

Cloud Data Architecture Design & Strategy: Design and implement secure scalable cloud-based data pipelines data warehouses and data lakes. Drive the selection and integration of cloud data services (e.g. storage databases analytics tools). Develop comprehensive cloud data strategies in alignment with business goals. Diagramming & Documentation: Produce clear and informative visual diagrams (e.g. data flow diagrams entity-relationship diagrams system architecture diagrams) to guide implementation and knowledge sharing. Maintain detailed documentation of data architecture design decisions and processes. Hands-on Implementation & Optimization: Actively contribute to the hands-on implementation of cloud data solutions. Proactively identify and implement performance optimization strategies for cloud data systems. Troubleshoot and resolve issues related to data pipelines data quality and data accessibility.

Description

The Cloud Data Architect will be a key contributor to designing, evolving, and optimizing our company's cloud-based data architecture. This role requires a strong background in data engineering, hands-on experience building cloud data solutions, and a talent for communicating complex designs through clear diagrams and documentation.

Responsibilities

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Minimum of 5 years of hands-on data engineering experience using distributed computing approaches (Spark, Map Reduce, DataBricks)
• Proven track record of successfully designing and implementing cloud-based data solutions in Azure
• Deep understanding of data modeling concepts and techniques.
• Strong proficiency with database systems (relational and non-relational).
• Exceptional diagramming skills with tools like Visio, Lucidchart, or other data visualization software.
• Preferred Qualifications
• Advanced knowledge of cloud-specific data services (e.g., DataBricks, Azure Data Lake).
• Expertise in big data technologies (e.g., Hadoop, Spark).
• Strong understanding of data security and governance principles.
• Experience in scripting languages (Python, SQL).

Educational Requirements

• Machine Learning Model Deployment
• 2) Familiarity with ETL tools ( Adobe Dart)
• 3) Any web-based analytics tool experience like Google Analytics, Adobe Analytics, Omniture
• 4) AWS certifications (e.g., AWS Certified Big Data - Specialty) and experience with Azure Databricks are highly desirable.

Experience Requirements

• Actively contribute to the hands-on implementation of cloud data solutions.
• Proactively identify and implement performance optimization strategies for cloud data systems.
• Troubleshoot and resolve issues related to data pipelines, data quality, and data accessibility.
• Required Qualifications:
• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Minimum of 5 years of hands-on data engineering experience using distributed computing approaches (Spark, Map Reduce, DataBricks)
• Proven track record of successfully designing and implementing cloud-based data solutions in Azure
• Deep understanding of data modeling concepts and techniques.
• Strong proficiency with database systems (relational and non-relational).
• Exceptional diagramming skills with tools like Visio, Lucidchart, or other data visualization software.