AI Data Engineer
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Job Description
AI Data Engineer bridging data warehousing and AI-driven analytics capabilities. Collaborating on automated solutions and operational workflows in eCommerce with global brands.
Responsibilities:
- Query, extract, and transform data from the data warehouse (BigQuery) to answer complex, multi-dimensional business questions spanning inventory, organic sales, traffic, sponsored ads, and DSP.
- Understand the full schema of the data warehouse — which tables hold what data, how they relate to each other, and what joins are required for accurate cross-domain analysis.
- Partner with internal teams to identify the most common and highest-value analytical questions clients and team members need answered.
- Design and build automated data pipelines and queries that feed AI tools with clean, structured, and contextually appropriate data.
- Develop and refine Claude Skills and Gemini Gems that enable conversational AI to conduct reliable eCommerce data analysis — working directly with prompt engineers to encode analytical methodologies into AI workflows.
- Collaborate with prompt engineers to document best practices for data analysis (statistical methods, benchmarking approaches, trend identification) so that AI tools can replicate expert-level thinking.
- Continuously improve and validate AI-generated outputs against manual analysis to ensure accuracy and trustworthiness.
- Help automate recurring analytical workflows into chatbot-style interfaces that the broader team can use without SQL knowledge.
- Identify operational bottlenecks and repetitive tasks across the business, then design and deploy AI agents to automate them — from data reporting to client deliverable generation to internal workflow management.
- Build, test, and maintain AI agents using Claude (Claude Code, Claude Co-work) and Gemini, ensuring they perform reliably and are adopted by the team.
Requirements:
- Strong proficiency in SQL — complex queries, multi-table joins, window functions, CTEs.
- Working proficiency in Python for data manipulation and analysis (Pandas, NumPy, or similar).
- Familiarity with JavaScript and JSON file structures.
- Hands-on experience with Google BigQuery.
- Experience working with or developing for large language models — specifically Gemini (Gems) and/or Claude (Claude Code, Claude Co-work, Skills).
- Hands-on experience building and managing AI agents that automate business processes and routine tasks.
- Strong understanding of data warehousing concepts: schema design, table relationships, data modeling.
- Ability to translate business questions into precise, efficient queries and then into AI-readable instructions.
- Enough business acumen and operational awareness to independently identify automation opportunities — not just execute on what’s handed to you, but see what’s broken or slow and propose a solution.
- Familiarity with digital commerce or eCommerce data (sales, advertising, inventory, traffic metrics) — does not need to be Amazon-specific but should understand the domain.
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