Azure Databricks Architect (Blue Ash)VBeyond Corporation • Blue Ash, OH, US
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Azure Databricks Architect (Blue Ash)
VBeyond Corporation • Blue Ash, OH, US
[job_card.variable_days_ago]
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[job_card.part_time]
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Required Qualifications :
Bachelors degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
At least 11 years of experience with Information Technology.
Proven years of hands-on experience in architecting solutions on Azure, Databricks and Spark
Proficiency in data engineering tools : Spark, Kafka, Airflow, SQL, Python.
Strong understanding of retail or CPG data domains
Familiarity with vector search and semantic retrieval for retail use cases.
Expertise in data privacy and compliance in consumer-facing environments
Good experience in end-to-end implementation of data warehouse and data marts
Strong understanding of Data Warehousing concepts of Data Vault, Dimensional modelling, OLAP design
Extensive experience with CI / CD platforms such as GitLab CI, GitHub Actions, AWS CodeBuild, Azure Pipelines, and Jenkins
Experience designing and implementing complex solutions for distributed systems
Experience in leading and mentoring teams
Preferred Qualifications :
Experience in Relational Modeling, Dimensional Modeling and Modeling of Unstructured Data
Familiarity with log and monitoring solutions
Experience in utilizing development containers, unit testing / code quality review / linting - standard best practice
Good understanding of Agile software development frameworks
Strong communication and Analytical skills
Ability to work in teams in a diverse, multi-stakeholder environment comprising of Business and Technology teams
Experience and desire to work in a global delivery environment
Experience with Generative AI frameworks : OpenAI, Hugging Face, LangChain
Knowledge of Model Context Protocol (MCP) or similar AI integration standards.
Experience and detailed knowledge with Master Data Management, ETL, Data Quality, metadata management, data profiling, micro-batches, streaming data loads
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