Head of Data - Remote

Head of Data -Remote

Full-time  | Remote: Must be based within CET +3h max | Regular travel to Geneva | Employment via Employer of Record

DLG builds LuxuryIQ, a market intelligence platform used by 80+ luxury brands. The platform ingests data from 50+ sources — social platforms, search engines, secondary markets, advertising networks — through BigQuery into client-facing analytics and AI-powered tools.

The data infrastructure exists and runs in production. It needs an experienced engineer to take ownership, improve reliability, expand coverage, and enforce quality standards across the full pipeline.

What makes this different: your clean, documented data will power a conversational AI layer (via Model Context Protocol)  and a SaaS solution that lets luxury brand CEOs query market intelligence in natural language. You’re not building another analytics pipeline — you’re building the foundation of an AI product.

SCOPE  ●

You own the data lifecycle from ingestion to delivery. You hand off clean, documented data to the platform engineering team. Clear boundary: you own everything up to the handoff; platform engineering owns what happens after.

You own the budget for the data function (vendors, infrastructure, tooling).

• Ingestion: Build and maintain crawlers, API integrations, and vendor data feeds. Monitor collection reliability. Onboard new data sources within planned timelines.
• Transformation: Manage the full pipeline (from raw to production). Implement automated QA at every stage.
• Delivery: Maintain schema integrity in BigQuery (primary), PostgreSQL, and regional databases (China). Ensure downstream consumers — including the MCP/AI layer — receive consistent, queryable, documented datasets.
• Documentation: Document every transformation rule, edge case, and business logic decision. The goal: any question about data behaviour can be answered from the spec, not from someone’s memory.

CURRENT ENVIRONMENT  ●

• Warehouse: BigQuery (Google Cloud)
• Databases: PostgreSQL (LuxuryIQ SaaS), regional databases (China)
• Sources: 50+ (social, search, secondary market, advertising, catalogue)
• Pipeline: 6-layer architecture  in production
• Team: Currently 6-person data team in place and hiring
• AI integration: Model Context Protocol (MCP) connecting BigQuery to LLM-powered client tools

REQUIREMENTS  ●

Technical

• SQL fluency (BigQuery preferred)
• Python for pipeline orchestration, transformation, and validation
• Data modelling and schema design for multi-source, multi-market datasets
• Web scraping, crawler development, and API integrations
• Entity resolution and deduplication across heterogeneous data sources
• Working knowledge of AI/LLM tooling (Claude Code, Copilot, or equivalent)

Behavioural

• You take full ownership of your scope and drive it independently
• You identify gaps in pipeline coverage and close them systematically
• You document thoroughly because undocumented systems are unreliable systems
• You treat data quality as non-negotiable — you’ve been burned by bad data before and it shows

IDEAL BACKGROUND  ●

You’ve worked with scraped, unstructured, messy real-world data at scale. You know what it’s like to reconcile the same entity across dozens of sources with different naming conventions, missing fields, and inconsistent formats.

Strong-fit industries: Price comparison and travel aggregation platforms, marketplace intelligence and web analytics, real estate platforms, alternative data providers for finance, or competitive intelligence companies.

The key differentiator: Have you built a data product that external customers pay for? That’s a different mindset than running internal data ops. Interest in the luxury industry is a plus but not required — the data engineering challenges are universal.