Senior Data Engineer (Data Platform)
Senior Data Engineer on a newly formed Data Platform team owning continuous governance of the data model behind Mico Engage AI: analyzing entity design and access patterns across TiDB and Aurora, building lineage/benchmark/ADR tooling, enforcing data retention deletion, offloading aggregation to Snowflake with reverse-ETL, and restoring test reliability. Core stack: SQL/MySQL-compatible RDBMS, Sno
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's degree or above in computer science, information engineering, or related field (equivalent practical experience accepted)
- 5+ years of professional experience in backend or data engineering
- Backend development experience (at least 3-5 years)
- Advanced SQL, relational data modeling, schema design, normalization/denormalization judgment, and index design
- Operating and tuning MySQL-compatible RDBMS (Aurora MySQL, TiDB): execution plans, slow-query fixes, index impact, safe DDL on large tables
- Able to trace data access paths and dependencies through a large, under-documented codebase and turn them into diagrams/documentation
- Experience identifying and fixing root causes of flaky tests (parallel execution conflicts, singleton leakage, insufficient isolation of external dependencies like Redis)
- Working experience with CI (GitHub Actions, etc.) and containers (Docker)
- Experience designing own benchmarks or profiles and demonstrating improvement quantitatively
- Professional AWS experience (primarily Aurora/RDS, S3, IAM, networking)
- Professional experience with monitoring and alert design, on-call, incident response, and root cause analysis
- Disposition to argue from measurement rather than assertion
- Ability to align directly with the business side (CE/CS) and product and land changes with business impact
- Habit of treating documentation and ADRs as an asset rather than a burden
- Ability to develop junior engineers on technical and non-technical fronts
Nice to have
- TypeScript / Node.js: production-grade code; implementing and refactoring within a large monorepo and shared libraries
- Experience operating and tuning distributed SQL databases such as TiDB (GC, region splitting, chunk sizing)
- Experience building aggregation pipelines on Snowflake and designing/operating reverse-ETL
- Experience designing and executing production data deletion under a retention policy; PII classification and data design informed by APPI or GDPR
- Experience automating data lineage extraction (e.g. static code analysis) and generating documentation with mermaid/d2
- Experience managing infrastructure as code with Terraform, AWS CDK/CloudFormation
- Experience with legacy modernization: splitting a monolith, dismantling a shared library, or phased migration without service interruption
- Day-to-day use of ADRs, design docs, and runbooks
- Experience collaborating with database or warehouse vendor specialists on consequential technical decisions
- Community involvement: OSS contributions, technical writing, speaking at meetups or conferences
Full description
**Senior Data Engineer（Data Platform）
About Mico
**Mico's mission is to empower every brand by building lifetime trust through humanlike technology. By 2030, we aim to be Asia's No.1 Brand Empowerment Company. Mico builds the conversational layer Japanese brands use to reach their customers — LINE, SMS/RCS, Voice AI and web — for more than 5,500 companies across finance, insurance, retail and real estate.Our four core values guide everything we do:
Wow the Customer
Invest in Passion
Beyond Borders
Be the Change
**About the Role
The Data Platform team was newly established in May 2026. Our mission is not a one-off cleanup of the data models in mmc-mono-repo — the codebase behind Mico Engage AI — but building a capability to govern them continuously**.
As a Senior Data Engineer, you will own — from investigation through implementation and production rollout — the analysis of entity design and access patterns across TiDB and Aurora, the build-out of our governance toolset (seven items: local reproduction environments, external-expert collaboration, data lineage, test reliability, benchmarks, the classification table, and ADRs), and the concrete work that takes load off TiDB: production deletion under a retention policy, event-attribute transformation, and offloading heavy aggregation to Snowflake with reverse-ETL back into Aurora.
Beyond that lies a succession of core entities such as customer and segment. This is not a greenfield analytics platform role. It is the work of safely reshaping the data model of a large system that is already running, on the basis of evidence.
What We Expect
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Take full ownership of the entities and tooling items in your scope — from investigation through architecture, implementation, production rollout, and steady-state operations.
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Base optimization decisions on measurement and lineage rather than experience and intuition, and write down the reasoning.
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Align directly with the business side (CE / CS) and product, and land changes with real business impact — such as deletions and segment-definition migrations — safely.
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Validate governance tooling on real cases, compounding it so that the next project is faster and safer.
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Build out lineage diagrams, runbooks, and ADRs so that new members can get productive on their own.
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Note how success is measured here: not "how many features shipped" but "how much the toolset's minimum-viable level rose." Phase-one output may look small — we are looking for someone willing to take that on with us.