Location & Work Schedule
Location: Indiranagar, Bangalore
Work Arrangement: Full-time, Work From Office
About M
At M - we’re early, ambitious, and moving fast. We’re building a new category in how urban households function. We help households run smoothly through trained professionals, operational excellence, and technology-driven support systems. Backed by Peak XV Partners, Blume Ventures and CRED we’re reimagining how homes run, so people never have to think about chores again.
The Role
M only gets smarter if the data does - own that.
Everything M knows about a household - what they order, what they've said, how they live - has to become clean, trustworthy signal the AI can learn from and act on. You'll own the data platform end to end: the pipelines, the models, the quality, the foundation the rest of the product's intelligence stands on.
What you'll do
- Own M's data platform end to end - ingestion, transformation, warehouse, and the analytics the whole company runs on.
- Turn messy real-world signals (orders, conversations, behavior) into structured, reliable data.
- Build the pipelines that feed M's memory and decisioning, where data quality directly shapes how good the AI is.
- Make analytics trustworthy at multi-tenant scale, without ever leaking one household's data across the boundary.
- Set the data standards and models the team builds on as we grow.
What We're Looking For
- 6-8 years in data engineering; you've owned a data platform, not just held a job in one.
- Deep querying and data modelling; strong with modern warehousing and pipelines.
- Experience keeping large, live datasets fresh and correct (streaming / CDC).
- You treat data quality and correctness as a first-class product concern.
- Comfortable being the person who defines how data works here.
Bonus Qualifications
- Built data foundations for AI/ML or analytics products.
- Worked with event-sourced or high-volume messaging data.
- Fluent at turning an ambiguous question into the data model that answers it.
30 / 60 / 90-Day Expectations
- 30 days: you've mapped our data end to end and shipped your first pipeline and quality improvements.
- 60 days: you own the core pipelines feeding analytics and the AI, and trust in the numbers is visibly up.
- 90 days: the data platform and its standards are yours - the team decides on data it trusts, and the AI learns from a cleaner foundation.