Data Engineer - Analytics & AI
Spectraforce
Los Angeles, CA, United States
1 day ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Data Analysis
Automated Storage and Retrieval Systems
Big Data
BigQuery
Cloud Computing
Extract Transform Load (ETL)
Data Warehousing
Python (Programming Language)
Machine Learning
Performance Tuning
+20 more
Power BI
Tensorflow
Search Technologies
SQL Databases
Tableau (Software)
Visual Analytics
Pytorch
Retrieval-Augmented Generation
Large Language Models
Snowflake
Agentic-AI
Build Management
Scikit Learn
Information Technology
Claude
Google Gemini
GPT
Data Pipelines
Api Management
Amazon Redshift
Job description
- Serve as a founding Data Engineer, partnering with internal and cross-functional teams to define analytical product features and requirements.
- Write and optimize SQL queries to retrieve and analyze large-scale datasets, surfacing actionable business insights.
- Design and build end-to-end ETL pipelines on cloud infrastructure using Python.
- Develop interactive dashboards in Tableau to visualize key metrics and support data-driven decision-making.
- Conduct ad-hoc analysis using SQL and Python to answer business questions and support partner teams.
- Train and test machine learning models for clustering, prediction, and other analytical use cases.
- Contribute to AI agent development using MCPs and APIs; test and optimize their performance.
- Develop RAG-based agents leveraging vector search and knowledge retrieval to support AI-driven insight discovery.
Requirements
- Bachelorβs degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 5+ years of hands-on experience with Python programming for building scalable data pipelines and ETL workflows on cloud infrastructure.
- 5+ years of experience with SQL query writing and performance optimization on large-scale datasets, using modern cloud data warehouse platforms (e.g., Snowflake, BigQuery, Redshift).
- 5+ years of experience building interactive data visualization dashboards (e.g., Tableau, Power BI, or similar tools).
- 4+ years of experience building and evaluating machine learning models using common frameworks (e.g., PyTorch, TensorFlow, scikit-learn)., * Masterβs degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 1+ year of hands-on experience developing GenAI/LLM-powered applications (e.g., GPT, Claude, Gemini), including designing AI agents, RAG pipelines, vector search/retrieval systems, and MCP or API integrations
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