Data Engineer – Analytics & AI

• 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.

Minimum Qualifications

• Bachelor’s 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).

Preferred Qualifications

• Master’s 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.