Senior Data & AI Platform Engineer

• Payments, settlement, reconciliation, fees, chargebacks, merchant reporting or finance-domain data.

• CRM-side data flows and reverse-ETL patterns, especially HubSpot, Salesforce, Zendesk or similar platforms.

• M&A or acquired-company data integrations: schema discovery, file/API ingestion, data profiling, master-data mapping, migration QA and reporting continuity.

• NoSQL-to-analytics modelling, including change-feed patterns from operational databases into lakehouse or warehouse structures.

• GA4, BigQuery export, Google Ads / SEM feeds, Segment or other event and marketing analytics sources.

• Experience with Azure OpenAI, LLMs, RAG, AI agents, prompt/version management or AI-assisted development workflows.

• Experience building AI-generated reporting, natural-language analytics, business copilots, automated insight generation or merchant/customer intelligence tools.

• Responsible AI and governance experience, including RBAC, PII handling, audit logs, human approval flows, explainability and GDPR-conscious design.

• Has owned a production data platform, not only built dashboards or one-off analytics projects.

• Can explain how they governed metrics and prevented conflicting definitions across teams.

• Has migrated or consolidated legacy reporting into a modern semantic layer without breaking business trust.

• Balances delivery urgency with reliability, documentation, cost control and operational resilience.

• Communicates clearly with executives, product teams, analysts and engineers; can say “no” or “not yet” with evidence.

• Is hands-on enough to debug pipelines and models, while senior enough to set standards and mentor others.

• Has used AI or automation in a real data-engineering context to speed up delivery, not just as a novelty, and can describe the guardrails they put around it.