Team: Data · Location: Bangkok (hybrid) · Reports to: Data Team Lead · Type: Full-time · Level: Junior–Mid (we calibrate the role and offer to your experience)

About Tokenomist

Tokenomist (a product of DAOSurv) is the crypto data platform for token supply: vesting and unlock schedules, emissions, allocations, and on-chain supply metrics. We turn messy, fragmented on-chain and market data into clean, reliable, point-in-time-correct datasets that traders, funds, exchanges, and protocols depend on to make decisions. We're a lean, technical team serving millions of users worldwide.

Trusted by traders and institutions across crypto, with paying institutional customers.

The role

We're looking for someone to keep our data flowing and trustworthy day to day. You'll operate and monitor our pipelines, safeguard data quality and coverage, handle backfills and reconciliation, and make sure the datasets our product and research teams rely on are accurate and up to date.

You'll work alongside our Senior Data Engineer, who owns the core architecture and will mentor you. There's a clear path to grow into deeper pipeline and engineering work as you take on more. We're open on level: strong juniors and new grads are welcome, and we'll scope the role up for candidates with more experience.

Why this role

• A rare way into crypto data. Learn point-in-time-correct data at the source, mentored one-on-one by a senior engineer.
• Real ownership early. You own the freshness and trustworthiness of datasets the whole product depends on, with visible work from week one.
• A path, not a plateau. A clear route to grow into full pipeline engineering as you take on more.

What you'll do

• Operate and monitor daily data pipelines; own the freshness, coverage, and uptime of our core datasets.
• Run routine data-quality checks and audits: catch, triage, and fix data issues, and reconcile our data against external sources (block explorers, market-data providers, etc.).
• Handle backfills, catch-ups, and reprocessing while preserving point-in-time correctness.
• Write and maintain SQL transformations (and dbt models) that shape raw data into the metrics product and research need.
• Keep documentation, runbooks, and data-quality reporting current.
• Grow into independent pipeline development and ownership of your own areas, with support from the senior engineer.

What we're looking for