TL;DR

The bad

⚡️ We hire slow and fire fast
😪 No flashy merch or trips
👷🏻 Hard work
✋🏻 No stock (usually)
🗣️ English or Spanish required
👶🏻 No kindergarten standards

The good

🧑🏻‍🔬 AI | deep tech | multimedia | social
🌎 Fully remote
💵 Above market rate salary
⬆️ Not shy to promote
🍰 BIG cash bonuses
🔁 Rolling interviews
👴🏻 No condescending treatment

Who we are

😼 We are a small but very competitive startup.
We are incredibly visionary. Decently competent. Reasonably funded. Subpar at sticking to deadlines.

• Cool af: What we are building and how we are doing it are one for the history books.
• Chill af: Work remotely, manage your own time, skip work when you need to.
• 0% BS: 0% political behaviour, 0% bureaucracy, 0% pedantry, 0% ass-kissing.
• Give & Take: We won’t take a bullet for you but we’ll never throw you under the bus either.
• Not a: Family. But not a toxic elite team either. Just… a competitive yet reliable company.

The role

💼 No fixed role or rank.
You’ll partner with both our AI Research Scientist and business teams to make data flow and insights happen.

• Make the first move: Pitch how you’d architect our data platform.
• Expect negotiation: We’ll align on scope, timeline, and budget.
• Prove your worth: Show us past pipelines, dashboards, or analytics automations.

What you’ll do

🛠️ Turn raw data into gold. Just that.
Build, optimize, and maintain the data backbone for our research and business intelligence.

• Data ingestion & ETL: Connect, clean, and transform data from APIs, databases, and logs
• Pipeline orchestration: Schedule and monitor workflows with Airflow or Prefect
• Data modeling: Design analytical schemas, data marts, and semantic layers (dbt or similar)
• Business analytics: Build and tweak dashboards, track KPIs, automate metric alerts
• Research support: Provision datasets, feature stores, and evaluation pipelines for the AI team
• Ad-hoc analysis: Dive into data to answer product questions and guide strategy

How you’ll do it

🧠 Work smarter, not harder.
Automate, automate, automate. Do so with good taste, common sense and care.

• GPT: Ask our most senior and wisest advisor.
• Plan ahead: Plan first (even for yourself) → confirm when necessary → execute methodically.
• Be strategic: Not dogmatic. Not experimental. Choose results, find how to get them.
• Guidance: Collaborate directly with founder and exec advisors.
• Trends & best practices: Stay on top of modern data stack patterns…
• Notion: Organise your workflows with our chef’s-kiss Notion content planner and templates.
• Feedback: Iterate from metrics, insights, and team reviews.
• Rkive AI: Automate editing, publishing, and analytics with our own tool.
• Toolbelt: Python, SQL, pandas, Spark (or Dask), Airflow/Prefect, dbt, Looker/Metabase/Chartio, Git.

Who you are

💍 We want true love, not a marriage of convenience.
We don’t care about your seniority—just your ability to tame data.

• Data-obsessed: You thrive on pipelines, schemas, and clean metrics.
• Problem-solver: You break down questions into data tasks and deliver answers.
• Infrastructure savvy: You’ve built and monitored ETL and warehouses.
• Analytical: You love diving in with SQL and Python to uncover insights.
• Collaborative: You write clear docs, code, and queries—and teach others.
• Adaptable: You juggle research data needs and business analytics priorities.

When

🏡 Join as early as June 1, 2025 & as late as July 1, 2025.
We’re building for the long haul.

• Rolling interviews: We interview (and hire) as CVs arrive. First come first served.
• Bonus: Performance-based cash bonuses.

What

👀 Show us something worth seeing.
But most importantly, show us YOU. A data pipeline repo or dashboard link will land you an interview, not just a CV.

• CV: Focus on pipeline projects and analytics impact.
• Portfolio: Git repos, dashboard screenshots, dbt projects…
• Recommendations: From teammates, managers, or stakeholders.
• Cover letter: Tell us how you’d scale our data game!

Apply

Not sure? Swipe left ❌
Sounds like a dream? Hit us up ✅ 😉
Send your resume, portfolio, and GitHub links to careers@rkive.ai