Data Engineer

Summary

• 5+ years in data science or data engineering roles;
• Proficient in Python, SQL, and common data tools (Pandas, Plotly, Streamlit, Dash);
• Familiarity with large language models (LLMs) and deploying ML in production;
• This role is NOT focused on BI, data platforms, or research work;
• Good fit: Hands-on, Python-first Applied AI / GenAI engineers with real delivery ownership and client-facing experience;
• No fit: Data platform or BI profiles, architecture-heavy or lead-only roles, research-focused profiles, or candidates with only PoC-level GenAI exposure and no ownership.

Role:

This role is ideal for someone comfortable working throughout the entire pre-sales to delivery lifecycle, rolling up their sleeves to solve complex multi-faceted problems, thrives as a technical communicator, and works well as a key member of a team. 

Requirements:

• 5+ years in data science or data engineering roles;
• Proficient in Python, SQL, and common data tools (pandas, Plotly, Streamlit, Dash); 
• Familiarity with large language models (LLMs) and deploying ML in production;
• Experience working with APIs and interpreting technical documentation;
• Client-facing mindset with clear ownership of decisions and outcomes;