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