AI & Data Solutions Analyst

LEDGENT
San Diego, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 130K

Job location

San Diego, United States of America

Tech stack

Clean Code Principles
API
Software Applications
Azure
Information Systems
Data Architecture
Information Engineering
Data Infrastructure
ETL
Database Queries
Database Storage Structures
Data Flow Control
Python
Operational Databases
Power BI
Azure
Search Technologies
SQL Databases
Systems Integration
Scripting (Bash/Python/Go/Ruby)
Cloud Platform System
Microsoft Power Automate
Large Language Models
Powerquery
Pandas
Microsoft Fabric
AI Platforms
Information Technology
Data Analytics
REST
Software Version Control
Api Management
Databricks

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, Data Analytics, or related field.
  • 3-6 years of professional experience in data engineering, analytics engineering, or a BI/data platform role with a strong engineering component.
  • Demonstrated experience building production data pipelines on cloud-native platforms (Microsoft Fabric, Azure Data Lake, Databricks, or equivalent).
  • Hands-on experience building AI-powered applications or agents using LLMs, beyond basic prompting, including RAG architecture, vector search, API integration, or Copilot Studio/custom agent development.
  • Commercial real estate, real estate finance, or related industry experience preferred but not required.
  • Strong understanding of data architecture, data modeling, and ETL/ELT processes.
  • Experience building API integrations and automated workflows.

Desired Technical Skills

  • Microsoft Fabric / OneLake: Lakehouse architecture, Dataflow Gen2, Fabric Pipelines, Delta tables, DirectLake semantic model configuration.
  • SQL: Advanced query writing, data modeling, understanding of relational and columnar database structures.
  • Python: Data engineering and automation scripting (pandas, requests, pyarrow, API integration); ability to write clean, documented, maintainable code.
  • AI Platforms: Hands-on experience with Azure OpenAI Service, Azure AI Search (vector + hybrid search), Copilot Studio, or equivalent enterprise-governed LLM platforms.
  • Power BI: Dashboard development, DAX, Power Query, semantic model administration.
  • Power Automate: Complex workflow automation and system integration.
  • APIs: REST API design and consumption; ability to build and maintain custom connectors.
  • Version Control: Git/GitHub.

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