AI Data Engineer

Rockstar

About The Position

Rockstar is recruiting for a fast-growing eCommerce and Amazon services and technology company that partners with global brands to drive measurable growth across online retail marketplaces. Our client combines proprietary technology, deep marketplace expertise, and a trust-first approach to client service. They have maintained a high client retention rate and are scaling their team to match the ambition of their roadmap. They reward those who demonstrate excellence and consistency at every level. If you prove yourself, you’ll be met with more opportunity, more responsibility, and their full support in building your career forward. About the Role This role is seeking an AI Data Engineer who can serve as the critical bridge between the data warehouse, AI-driven analytics capabilities, and the operational workflows that power the business. This role is part data engineer, part data scientist, part prompt engineer, and part automation architect — you’ll need to deeply understand where and how to pull data from the database to answer specific business questions, train and configure AI tools (Claude, Gemini) to automate that analysis at scale, and build AI agents that eliminate repetitive operational work across the organization. This means understanding which tables within the data warehouse hold the best data to answer specific questions, what joins are needed for multi-dimensional queries across inventory, organic sales, traffic, sponsored ads, and DSP — and then translating that knowledge into AI-readable instructions. You’ll draft Claude Skills, Gemini Gems, and structured prompts that enable the team (and eventually clients) to get accurate, nuanced answers from a conversational interface. Critically, this role requires someone with enough business sense and operational awareness to look at how teams work day-to-day, identify processes that can be automated, and build AI agents to handle them. You won’t just be handed a list of things to automate — you’ll be expected to spot the opportunities yourself and translate them into working solutions.

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.

Nice To Haves

Experience with Amazon Ads API data, DSP reporting, or marketplace analytics platforms.
Background in data science — statistical analysis, regression, forecasting, segmentation.
Experience building internal tools, dashboards, or chatbot interfaces.
Prompt engineering experience with structured outputs (JSON mode, tool use, system prompts).
Experience with MCP (Model Context Protocol) servers, API integrations, or connecting AI tools to external data sources.

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.