Role Technical AI Azure Python Data Engineer
Location Philadelphia PA
Experience 8 to 10 years
Role Overview
AI Azure Python Data Engineer t will play a key role in designing building and evaluating AI driven solutions that support innovation across the organization This individual will work at the intersection of applied AIML data engineering and business collaboration
This role requires someone who is highly adaptable comfortable operating in ambiguity and eager to learn new tools and approaches as needs change
Primary Skills
Strong proficiency in Python
Solid understanding of foundational AIML concepts including
Retrieval Augmented Generation RAG
Natural language SQL workflows
Vector databases
Agentic AI development frameworks framework agnostic ability to learn new ones
Experiment design and evaluation methodologies
Secondary Skills
Natural Language Processing NLP
AB testing and experimentation frameworks
Basic machine learning modeling
Design and run experiments to evaluate model and system performance
Collaborate with cross functional teams to identify and prioritize AI use cases
Continuously evaluate emerging AI tools and frameworks and recommend practical applications
Helpful Experience
Applying generative AI to classification and information extraction problems
Using generative AI for aggregation and synthesis use cases eg summarization or multisource synthesis systems such as Lumen
Designing and deploying agentic AI systems
Critical Traits for Success
Adaptability Growth Mindset Essential This role will evolve over time The ideal candidate is comfortable with shifting responsibilities and changing priorities as innovation initiatives develop
They must be willing and able to learn new tools techniques and domains quickly
Comfort with Ambiguity Innovation work often lacks predefined paths
The candidate should be comfortable operating without fully defined playbooks and helping shape direction as projects mature
Intellectual Humility Curiosity The ability to ask questions even at the risk of looking uninformed is essential Progress depends on proactively seeking knowledge from subject matter experts and other teams
Relationship Building Influence Success in this role requires building strong relationships across teams
The candidate should be personable collaborative and capable of appropriately following up and driving momentum when needed
Question Walk me through a recent end to end data solution you designed and delivered using Python starting from requirements to data ingestion transformation validation and serving consumption
What were your key architecture decisions and why
What it qualifies Real ownership architectural thinking ability to articulate tradeoffs and maturity expected from a tech architect
Question In Python based data pipelines what are the most common causes of performance bottlenecks and data quality issues youve seen How did you detect them and what specific steps did you take to optimize runtime and improve reliability
Question As an onsite tech architect you ll handle ambiguous asks from business users Tell me about a time you translated unclear stakeholder requirements into a data model solution design including governance security considerations and drove alignment across multiple teams
Skills
Mandatory Skills : MS SQL Server Python Python - Data Science Python for DATA Vector Databases and Embedding
Good to Have Skills : AI/GenAI Research Azure AI Studio Azure Analysis Services MySQL Natural Language Processing - AIOPS
Role Technical AI Azure Python Data Engineer Location Philadelphia PA Experience 8 to 10 years Role Overview AI Azure Python Data Engineer t will play a key role in designing building and evaluating AI driven solutions that support innovation across the organization This individual will work ...
Role Technical AI Azure Python Data Engineer
Location Philadelphia PA
Experience 8 to 10 years
Role Overview
AI Azure Python Data Engineer t will play a key role in designing building and evaluating AI driven solutions that support innovation across the organization This individual will work at the intersection of applied AIML data engineering and business collaboration
This role requires someone who is highly adaptable comfortable operating in ambiguity and eager to learn new tools and approaches as needs change
Primary Skills
Strong proficiency in Python
Solid understanding of foundational AIML concepts including
Retrieval Augmented Generation RAG
Natural language SQL workflows
Vector databases
Agentic AI development frameworks framework agnostic ability to learn new ones
Experiment design and evaluation methodologies
Secondary Skills
Natural Language Processing NLP
AB testing and experimentation frameworks
Basic machine learning modeling
Design and run experiments to evaluate model and system performance
Collaborate with cross functional teams to identify and prioritize AI use cases
Continuously evaluate emerging AI tools and frameworks and recommend practical applications
Helpful Experience
Applying generative AI to classification and information extraction problems
Using generative AI for aggregation and synthesis use cases eg summarization or multisource synthesis systems such as Lumen
Designing and deploying agentic AI systems
Critical Traits for Success
Adaptability Growth Mindset Essential This role will evolve over time The ideal candidate is comfortable with shifting responsibilities and changing priorities as innovation initiatives develop
They must be willing and able to learn new tools techniques and domains quickly
Comfort with Ambiguity Innovation work often lacks predefined paths
The candidate should be comfortable operating without fully defined playbooks and helping shape direction as projects mature
Intellectual Humility Curiosity The ability to ask questions even at the risk of looking uninformed is essential Progress depends on proactively seeking knowledge from subject matter experts and other teams
Relationship Building Influence Success in this role requires building strong relationships across teams
The candidate should be personable collaborative and capable of appropriately following up and driving momentum when needed
Question Walk me through a recent end to end data solution you designed and delivered using Python starting from requirements to data ingestion transformation validation and serving consumption
What were your key architecture decisions and why
What it qualifies Real ownership architectural thinking ability to articulate tradeoffs and maturity expected from a tech architect
Question In Python based data pipelines what are the most common causes of performance bottlenecks and data quality issues youve seen How did you detect them and what specific steps did you take to optimize runtime and improve reliability
Question As an onsite tech architect you ll handle ambiguous asks from business users Tell me about a time you translated unclear stakeholder requirements into a data model solution design including governance security considerations and drove alignment across multiple teams
Skills
Mandatory Skills : MS SQL Server Python Python - Data Science Python for DATA Vector Databases and Embedding
Good to Have Skills : AI/GenAI Research Azure AI Studio Azure Analysis Services MySQL Natural Language Processing - AIOPS
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