Senior Data Engineer - Internal Platform

Parloa; Berlin; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

Parloa, located in Berlin, is seeking a Senior Data Engineer to build and scale the data infrastructure that supports its AI initiatives. The successful candidate will manage the Databricks workspace and maintain automated data ingestion pipelines from various systems. Proficiency in Python, SQL, and ETL tools is required. The role involves defining KPIs for AI adoption and ensuring GDPR compliance. Join us to drive innovation in data engineering at Parloa.

Qualifikationen

• Experience designing data layers that power AI/LLM-based applications.
• Proficiency in Python, SQL, ETL/ELT tools, and MLOps.
• Knowledge of dimensional modeling and modern data warehouse technologies.
• Ability to comprehend complex requirements and resolve performance issues.
• Ability to articulate complex technical concepts to non-engineering audiences.

Aufgaben

• Own the internal-facing Databricks workspace end-to-end.
• Build and maintain Airbyte pipelines for automated data extraction.
• Implement architecture for clean, trusted datasets.
• Partner with AI Transformation Team for data enablement.
• Define and build KPIs for tracking AI adoption and impact.
• Own data classification and compliance processes.

Kenntnisse

Data layers design for AI applications

Python

SQL

ETL/ELT tools

MLOps

Dimensional modeling

Data governance

Data compliance

Jobbeschreibung

About the role

Senior Data Engineer – Internal Platform. Build, own, and scale the data infrastructure that powers Parloa’s internal AI transformation. Create a unified, self‑serve data access layer that delivers business context to AI agents and teams. Define KPI metrics and dashboards for leadership to track AI adoption and business impact.

Areas of ownership

• 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 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.

Who you are

• 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 efficient use.

Parloa is an e‑verify employer in the USA. All employees uphold GDPR, ISO 27001, and other data protection standards. * We provide equal opportunities to all qualified applicants regardless race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background and other characteristics.