Lead Data Engineer - Internal Platform

About the role

As Lead Data Engineer – Internal Platform, you will build and own the data infrastructure that powers Parloa's internal AI transformation. Today, business-critical data lives across dozens of disconnected tools with no unified way to access it — you'll change that by creating a single, self-serve access layer that gives AI agents and teams the business context they need to operate.

What you'll do

• Own the Internal-facing Databricks workspace end-to-end: configuration, compute, access controls, and cost management.
• Build and maintain Airbyte pipelines that pull data from Salesforce, Gong, HRIS, finance systems, and other tools on automated schedules.
• Implement the architecture that turns raw data into clean, trusted, analysis-ready datasets.
• Partner with the AI Transformation Team to ensure AI agents and LLM workflows get the right data in the right format.
• Define and build the KPIs and dashboards that track AI usage, proficiency, and business impact across the company.
• Own data classification, access policies, GDPR/DPA compliance, and pipeline monitoring.

What you'll need

• Experience designing data layers that power AI/LLM-based applications and agentic workflows.
• Proficiency in Python, SQL, ETL/ELT tools, and MLOps.
• Knowledge of dimensional modeling and modern data warehouse technologies.
• Ability to articulate complex technical concepts to non-engineering audiences.
• Ability to define and instrument AI adoption KPIs: usage tracking, proficiency distribution, and business impact metrics.
• Understanding of how AI tools consume data – context windows, retrieval patterns, embedding pipelines – and how to optimise data access.