DLG (Digital Luxury Group)

• You own the data lifecycle from ingestion to delivery. • You hand off clean, documented data to the platform engineering team. • You own the budget for the data function (vendors, infrastructure, tooling). • Build and maintain crawlers, API integrations, and vendor data feeds. • Monitor collection reliability. • Onboard new data sources within planned timelines. • Manage the full pipeline (from raw to production). • Implement automated QA at every stage. • Maintain schema integrity in BigQuery (primary), PostgreSQL, and regional databases (China). • Ensure downstream consumers — including the MCP/AI layer — receive consistent, queryable, documented datasets. • Document every transformation rule, edge case, and business logic decision.

• You will design and ship production-grade AI agents and automated workflows that replace recurring high-volume work across performance media, creative production, social content, and account operations. • Performance media reporting automation: Replace manual monthly reporting with templated agents for Meta, Google, TikTok, LinkedIn, Pinterest, GA4, and Looker. • Quality control agents: Build brand checkers, copy validators, asset spec auditors, and campaign setup reviewers so our teams can ship quality work at scale without bottlenecking our senior team. • Per-client capability libraries: Structured files for our top accounts that codify brand voice, asset specs, deliverables, and quality standards. • Workflow automation: Map and automate the three to five highest-volume workflows across the agency, from brief to asset delivery. • Team enablement: Train five+ team members to ship or modify agents independently.

• Set the technical direction for pipeline architecture and data quality standards • Take end-to-end ownership of mission-critical pipelines — from raw ingestion through to clean, documented delivery in BigQuery • Be the go-to technical authority on data behaviour across the platform • Design and develop data processing, cleansing, transformation, and QA scripts using Python and SQL • Own the operation, maintenance, and enhancement of existing mission-critical data pipelines and ETLs • Monitor pipeline reliability and data quality standards; identify and close coverage gaps systematically • Optimise ETL performance and migrate legacy pipelines into a more scalable architecture • Define and enforce data quality standards across the full pipeline • Contribute to architectural decisions on ingestion, transformation, and delivery layer design • Own the full data lifecycle documentation: every transformation rule, edge case, and business logic decision must be spec'd • Fetch datasets from external data sources: REST APIs, JSON, CSV • Perform data migrations and batch data updates • Conduct exploratory analysis to support new business requirements and data source onboarding • Develop proof-of-concept pipelines for new data initiatives

• Conduct deep-dive investigations into new data sources to understand the "real-world" baseline and the business logic behind the data • Perform initial rounds of raw data validation against the source of truth for every new data source integrated into the platform • Ensure that the transition from "raw data" to "platform insight" maintains absolute integrity • Translate manual findings into automated solutions • Design and implement Python scripts, SQL automation rules, and proactive alerts • Build and maintain data health dashboards (Looker Studio/BigQuery) to identify anomalies before they reach the client • Develop continuous monitoring mechanisms to track data freshness, volume, and distribution • Act as the primary point of contact for Data Quality incidents reported by internal teams or external users • Perform root-cause analysis (RCA) to determine if issues stem from the raw source, ingestion pipelines, or processing logic • Collaborate with Data Engineers to resolve bugs and verify fixes, ensuring the data is corrected and re-processed accurately

• You'll be the bridge between product and revenue teams, translating our AI-powered market intelligence platform into compelling client-facing materials and market positioning. • Develop core positioning frameworks, value propositions for key buyer personas, taglines, and templated marketing materials for different use cases • Create comprehensive sales toolkit, including competitive battle cards, FAQs, and demo scripts • Conduct ongoing competitive analysis, produce differentiation documentation, monitor market and competitor movements, and translate insights into actionable positioning strategies • Build customer case studies, develop use case narratives across luxury verticals, and produce white papers that establish thought leadership • Lead product release announcements and feature communications, develop multi-channel activation plans, and ensure consistent messaging from internal teams to market • Produce product guides and documentation for internal teams and customers, and maintain internal knowledge base • Manage demo environment configuration, develop standardised demonstration narratives with vertical-specific customisation for watches & jewelry and fashion sectors

• Design and development of data processing, data cleansing, data transformation and QA scripts using Python and SQL • Operations, maintenance and enhancements of existing mission-critical data pipelines and ETLs • Monitoring and regular maintenance of data pipelines, ensuring data reliability and quality standards • Enhancements to meet evolving business requirements • Optimization of ETLs for performance • Migration of legacy data pipelines into more a scalable architecture • Typical data engineering responsibilities including SQL database design, maintenance and optimization • Fetching datasets from external data sources: REST API, JSON or CSV • Performing data migrations and batch data updates • Exploratory projects including Analysis of various datasets to support business requirements • Developing Proof-of-concept of new data pipelines • Working with other data team members to complete common deliverables and provide technical expertise