Senior Data Engineer – Customer Data Platform (Founding)

#1 on ProductHunt. Over 10,000 AI agents generated worldwide in just 3 months since launch – that's our voice AI agent platform "Omakase.ai."

Our motto: Always Be Launching. Elite global team, Work Super Hard, AI-driven development. Through these principles, we've achieved extraordinary growth at breakneck speed.

We've finally launched monetization and can see ARR on track to exceed $100K in our first month – we're confident we're on the trajectory for global domination. This is why we're hiring elite engineers to fight alongside us from Japan. Let's conquer the world together with a Japanese-born AI product!

Why This Role Exists

Omakase Voice AI turns voice‑first, LLM‑powered agents into genuine sales reps for e‑commerce brands. We hit #1 on Product Hunt and launched 10 k+ agents in three months—but real‑time data is still our oxygen. We’re hiring a founding data engineer to build the customer‑data platform that fuels our generative‑AI products—converting every click and conversation into actionable insight in seconds.

What You’ll Tackle in Your First 12 Months

• Design low‑latency pipelines – Build streaming and batch data flows in the cloud, choosing the technologies that best balance speed, reliability, and cost.
• Define our data contracts – Create the event‑tracking taxonomy and lightweight SDKs so every interaction is captured once and usable everywhere.
• Model customer identity & behavior – Deliver privacy‑safe schemas that unlock instant segmentation and personalization.
• Automate data quality – Put tests, lineage, and observability on autopilot so we can ship fast without breaking trust.
• Feed the AI agent in real time – Provide up‑to‑the‑second conversation context while the call is still live.
• Power insight loops – Build data flows that drive A/B tests, merchant dashboards, and product decisions.
• Expose clean APIs – Enable product and analytics users today—and future ML work—to self‑serve the insights they need.

 

Growth Opportunities

• Data architecture leadership – Shape the customer‑data roadmap and recommend build‑vs‑buy options alongside the co‑founding engineers.
• Compliance stewardship – Guide GDPR/CCPA/PIPL readiness and privacy best‑practices.
• Advanced modeling & ML foundations – Lead predictive analytics and personalization projects, and seed an in‑house ML capability as we mature.
• Team building – Hire and mentor future data engineers.

 

Must‑Haves

• 8+ years (ideally 10) building production data platforms.
• 2+ years with streaming systems (Kafka, Kinesis, Flink, Spark Streaming, or similar).
• Mastery of Python and SQL and at least one strongly typed language (Go, Java, or Scala).
• Cloud‑native experience (Docker/K8s or equivalent).
• Experience modeling data schemas for OLTP and OLAP workloads (relational, dimensional, graph).
• Clear English communication (Japanese welcome).
• Highly valued: hands‑on privacy/compliance work (GDPR, CCPA, PCI DSS).

Nice‑to‑Haves

• Built or maintained a CDP or feature store.
• Conversational‑AI, recommender, or real‑time ML pipelines.
• Differential privacy / clean‑room techniques.
• Previous zero‑to‑one startup ride.

Our Current Footing → Possible Next Steps & Rationale*

Layer	Today (Prod)	Possible Next Steps & Rationale
App	Ruby on Rails (Heroku)	Container‑based services
Data Store	PostgreSQL, BigQuery	Scalable data warehouse or other store you recommend
Orchestration	Heroku Scheduler	Workflow engine & analytics transforms (e.g., Airflow, Prefect, dbt)
Streaming	— (batch only)	Your chosen streaming platform
Processing	SQL & Python scripts	Distributed processing (e.g., Spark, Flink)
Infrastructure	Heroku	AWS, Kubernetes, Terraform, CI/CD pipelines

Technologies listed are illustrative—your evaluation will drive the final stack.

Team & Culture

• Two‑engineer founding core today; you’ll be the first dedicated data specialist.
• Weekly ship cycles, prod focus—Always Be Launching.
• High autonomy, minimal process.
• Shared on‑call until a formal rotation is set.
• We currently rely on best‑in‑class AI services (e.g., LLM APIs) rather than running our own models—you’ll help lay the groundwork to bring key ML capabilities in‑house over time.
• English‑first docs; JP speakers welcome.

Benefits & Working Conditions

• Hybrid in Tokyo (expect heavier office presence during major launches).
• Full social insurance, ¥20 k transport allowance, ¥20 k housing allowance (if eligible).
• JP national holidays, paid leave, summer break, year‑end/New Year, refresh leave.

Interview Process

Application → HR chat → Technical deep dive → CEO interview → Team panel → Offer

 

Ready to Build the Data Engine of Conversational Commerce?

If you can ship fast and own the data platform end‑to‑end, hit Apply—even if you don’t meet every single bullet. Passion, learning velocity, and diverse backgrounds matter most to us.