Qualifications

• Bachelor's degree in computer science (years attended and graduated on the resume)
• 5+ years of hands-on data engineering experience using distributed computing architecture (Spark, Map Reduce, DataBricks)
• Proven track record of successfully designing & implementing cloud-based data solutions in AZURE
• Deep understanding of data modeling concepts & techniques
• Strong proficiency in database systems (relational & non-relational)
• Exceptional diagramming skills with tools like: MS Visio, LucidChart, or other data visualization software.

Preferred Qualifications

• Advanced knowledge of cloud-specific data services (DataBricks, Azure Data Lake)
• Strong understanding of data security & governance principles
• Experience in Scripting languages (Python, SQL)
• Someone who's done a lot of Spark soft dev - Spark ETL coding in Databricks would be an ideal candidate

Job Description

This Data & Solutions Architect resource 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 & documentation.

Core Responsibilities Cloud Data Architecture Design & Strategy

• Design & implement scalable, secure cloud-based data pipelines, data warehouses & data lakes
• Drive the selection & integration of cloud data services (storage, databases, analytics tools)
• Develop comprehensive cloud data strategies in alignment with business goals

Diagramming & Documentation

• Produce clear & informative visual diagrams (ie: data flow diagrams, entity-relationship diagrams, system architecture diagrams) to guide implementation & 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 & implement performance optimization strategies for cloud data systems
• Troubleshoot & resolve issues related to data pipelines, data quality, & data accessibility