Senior Data Engineer

Role: Senior Data Engineer (Contract)
Location: Fully Remote (LatAm)

About us
We are building an intelligent ultra personalized travel companion app powered by advanced AI, designed to make every journey feel more intuitive, personalized, and truly rewarding. We're creating this for people just like us, those for whom travel isn't just a hobby or occasional escape, but a core part of who we are. It's in our DNA, the open road calls, the itch to explore new places runs deep, and the best stories come from real miles logged, unexpected detours, and moments that only happen when you're out there living it.

We want teammates who live that lifestyle, who draw from their own adventures to infuse the app with an authentic vibe and intuition that resonates with fellow travelers. If road trips, spontaneous getaways, discovering hidden gems, or turning long drives into meaningful experiences are woven into your life, not just something you read about, you'll bring the empathy, insight, and passion that turns good features into something users feel was built exactly for them. This role is about building for people like you.

About the Role
We are seeking a Senior Data Engineer who specializes in building greenfield data systems. We aren't looking for someone who spent the last five years maintaining pipelines someone else built-we need the engineer who drew the schema on the whiteboard on Day 1 and took it to production.
You will design our event tracking and data architecture from scratch. Rather than building traditional BI reporting pipelines, your work will directly power our core AI and recommendation engine, setting up the foundation for real-time feature processing, data collection, and model consumption.

What You’ll Do
Architecture from Scratch: Architect, build, and deploy our end-to-end data pipeline infrastructure and event-tracking system from the ground up.
Schema & Event Design: Define clean, scalable event schemas, data models, and tracking taxonomies tailored specifically for downstream AI/ML consumption.
Core Stack Ownership: Build high-performance processing jobs and storage layers using Python and PostgreSQL as the primary backbone.
AI Product Integration: Partner closely with our AI engineering team to feed high-quality structured data into vector stores, inference engines, and contextual recommendation loops.

What We’re Looking For
5+ years of dedicated data engineering experience, specifically in early-stage or startup environments.
Zero-to-One Experience: You have explicitly built event tracking and data pipelines from scratch at a startup. You can articulate why you chose specific architecture trade-offs.
Core Technical Stack: Deep proficiency in Python and advanced PostgreSQL (indexing, partitioning, performance tuning, query optimization, JSONB usage).
Anonymous-to-Known Stitching: Hands-on experience mapping anonymous user sessions to authenticated user profiles without losing attribution or historical behavioral data.
Entity Deduplication: Practical experience writing entity resolution algorithms/jobs to map messy, duplicate records from multiple sources into a unified canonical profile.
Data for AI / RecSys: Practical experience structuring event streams and data pipelines designed to feed machine learning models, contextual prompts, or recommendation engines-not just standard analytics dashboards.
Event Streaming & ETL: Solid grasp of event-driven architectures, asynchronous message queues, data ingestion, and pipeline orchestration.