About us
Dashmote builds AI-native, agentic data products for both Fortune 500 brands (Coca-Cola, Heineken, Red Bull) and growth-oriented businesses. With offices in Amsterdam, New York, and Shanghai, we run two products: Location Intelligence (120+ data points per outlet across 30+ countries) and Food Delivery for optimising Sales & Marketing. We pair both with AI agents that work alongside our clients’ commercial, sales, and insights teams to find, score, and convert the right opportunities. As we scale up our multi-year global data pipeline, our Shanghai sourcing team remains the core engine behind every data product we ship.
The Role & Responsibilities
Your Mission
This role is a rare combination: a technical engineer, a product owner, and a business thinker in one person. Our Shanghai sourcing team runs large-scale web scraping across food delivery platforms, maps, and social media in 30+ countries, including serious anti-bot challenges. The team solves hard technical problems well; you bring the structure and judgment around it.
Your mission is to make sourcing delivery predictable: risks surfaced early, data issues caught before release, and stakeholders always knowing the current scope, quality, and timing.
What You Will Own
1. Technical Depth (Master the System & Its Logic):
You write Python, understand proxies and anti-scraping, and master the difficult logic behind every delivered number deeply enough to challenge the team: Finder completeness (grid coverage, full-grid vs hash-only refresh, and what it does to outlet counts), closed-outlet detection, new-outlet flags between refreshes, deduplication, and refresh/optimization strategy per source (frequency, incremental vs full crawls, request budgets). You document this logic and progressively productize it into repeatable rules per source.
2. The Product Owner (Own Planning, Quality, & Delivery):
One source-of-truth backlog and delivery tracker for all sourcing work. You run sprint planning with estimation: every task has an owner, an estimate, and a committed ETA. You own intake discipline (every request enters with a business owner, use case, acceptance criteria, and priority; urgent work displaces something explicitly), and you set sprint and monthly goals ranked by business value. You define measurable quality thresholds per source (coverage vs expected universe, closed-outlet rate, duplicate rate, freshness, field completeness), own the QA gates that run before any delivery leaves the team, and the monitoring on continuous pipelines (freshness, volume, last-green-run) so a stalled pipeline is detected in hours, not weeks.
3. The Business Thinker (Own Communication & Impact):
You are the single point of delivery communication: a weekly delivery update to the Amsterdam product and client teams on a fixed cadence (shipped, in flight, at risk), fast incident communication when a feed breaks, and a change protocol: any methodology, scope, or schema change that affects downstream data is impact-analyzed, communicated, and signed off BEFORE cutover. You know which client and deliverables consume every source; before a technical or scope change, you quantify which client-facing numbers move and by how much, and what it does to infra cost. Any coverage scale-up comes with a cost projection first (cost per source, per refresh, compute-hours).
4. The Working Style (AI-First):
You run the team's operations AI-first and set the example: AI agents for status reporting, QA assistance and anomaly detection, documentation, and scraper prototyping. You are accountable for defining where AI output is allowed and where human review is mandatory: AI-written code reaches production only through tests and QA gates. You continuously move manual operational work to agents, so the engineer's time goes to hard sourcing problems.
Authority & Boundaries
-
You own WHAT and WHEN: Backlog, priorities, acceptance criteria, QA gates, release readiness, and all delivery communication.
-
The Technical Owner owns HOW: Architecture, scraping methodology, proxy strategy, and engineering standards. You don't design the systems; you own the business rules and acceptance criteria they must satisfy. No technical change that alters delivered data ships without your signoff loop.
-
The Team Lead owns WHO: People management, hiring, and coaching. You manage tasks, not people.
-
Delivery dates are set jointly: You bring priority and the commercial deadline, the TO brings effort and technical risk, the Team Lead brings capacity.
-
Your explicit authority: Reject unclear requests, block deliveries that fail agreed QA gates, require signoff for data-affecting changes, and escalate visibly when committed work exceeds capacity.
You do not own: People management, compensation, engineering, architecture, or final commercial commitments to clients.
Job Requirements
Must Have
-
4+ years in data acquisition, web scraping, data platforms, or related technical product or delivery roles, with ownership of recurring delivery outcomes where freshness, completeness, and schema stability mattered.
-
Experience planning and managing large-scale data collection from multiple sources: scope, milestones, quality standards, and operational workflows.
-
Has defined acceptance criteria and quality standards for technical/data work (not only written business requirements), and has handled a production data-quality incident end-to-end.
-
English as a working language: Ability to lead weekly video syncs with the Amsterdam product and delivery teams and write clear written status updates in English.
-
Hands-on Python: Comfortable writing and reviewing scripts for QA, data validation, and workflow automation, and reading logs, SQL output, and scraper run summaries well enough to challenge assumptions. Solid grasp of network fundamentals and how proxies work. Note: You are not the primary production scraper engineer.
-
Daily user of AI tools (coding assistants, LLM workflows) with the judgment to know where human review is mandatory.
-
Ability to absorb complex data/system logic quickly (coverage completeness, entity lifecycle flags, refresh strategies) and explain it accurately to non-technical stakeholders.
Nice to Have
-
Independently built or led a web scraping framework (Scrapy or similar); web/mobile reverse engineering or API traffic analysis; anti-bot experience.
-
Hands-on data observability or monitoring tooling implementation.
-
Cloud infrastructure, task queues, workflow orchestration, distributed crawling, and FinOps exposure.
-
Has deployed LLM agents into shared production/team workflows (beyond personal use)
-
Strong product owner mindset, highly self-driven, and strong execution skills. Able to 'fly high and fly low': set the plan, and dive into the data when needed.
What's in it for you
-
Great office location right in the city center of Shanghai (near Jiangsu Rd metro station).
-
Dashmote Flex: A mix of working from home and the office + 20 days of working remotely (anywhere in the world!).
-
A competitive annual leave entitlement
-
Annual Company Health Check.
-
Company Laptop provided
-
Referral Bonus
-
Annual Learning Budget for your personal development.
-
Working for a company that was awarded the best B2B startup in Europe by Google, McKinsey, and Rocket Internet.
-
An exciting, international, and young work atmosphere that truly values your contribution, with an awesome culture of responsibility and plenty of fun team events and snacks.
If this sounds like a match, we would love to hear from you!
