Senior Data Engineer - Internal Platform

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision;
Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like , Health Equity, Allianz, SAP, Barmenia Gothaer, and TUI already deploying Parloa at scale.

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. Working closely with the AI Transformation Team and stakeholders across the non‑engineering organization, you’ll also define the KPIs and dashboards leadership uses to track AI adoption and impact.

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

• 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 comprehend and execute on complex requirements and resolve performance issues.
• Ability to articulate complex technical concepts to non-engineering audiences, making data architecture decisions and trade-offs understandable for leadership and cross-functional stakeholders.
• Passion for staying updated and driving innovation in data engineering.
• 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 for them.

Parloa is committed to upholding the highest data protection standards for our clients and employees’ data. Our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information.

We provide equal opportunities to all qualified applicants regardless of race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background, and other characteristics.