Mappa
Senior Data Engineer (AI-First Platform)
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Senior Data Engineer (AI-First Platform)
Senior Data Engineer (Remote)
Position Overview
We are looking for a brilliant, high-seniority Senior Data Engineer who is passionate about AI and eager to own the intersection of data science infrastructure and massive-scale data processing.
In this role, you will be responsible for architecting and orchestrating our data layers to handle extremely high volumes of unstructured data (video, images, and raw metrics) while building the infrastructure needed for our in-house AI agents to thrive.
Core Projects & Responsibilities
You will step in to own three major pillars from day one:
- In-House Social API Integration Transition our data ingestion from third-party social media API providers into a robust, scalable, and fully managed in-house pipeline.
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High-Volume Infrastructure & Architecture Engineer, scale, and optimize data layers and orchestration to safely store, clean, and process massive daily volumes of video, image, and raw performance data.
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LLM & Agent-Friendly Datasets Tackle the unique technical challenge of managing and structuring natural language data (including Markdown files and unstructured layers) to serve as optimized, high-context alternative datasets for our in-house AI agents.
Requirements & Qualifications
- Experience: 5+ years of experience in Data Engineering, ideally within fast-paced startup environments or AI-centric companies.
- Communication: Excellent, highly confident English communication skills (priority—pitching ideas, cross-functional collaboration, and documentation included).
- Core Technical Stack: Advanced proficiency in Python and PostgreSQL is mandatory.
- Data Architecture: Hands-on experience with data orchestration tools, database optimization, and managing large-scale data pipelines.
- AI/LLM Curiosity: Deep interest or prior experience in understanding how data pipelines and natural language datasets interact with Large Language Models (LLMs).
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Location & Working Hours Flexibility
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UK-Based (Preferred) Hybrid model (3 days on-site at our South London WeWork, near Waterloo Station). Hours: London time, with a slight late shift to overlap with international teammates.
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Latam-Based 100% remote, working hours align with PACIFIC STANDARD TIME (PST).
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