Senior Data Engineer - Internal Platform

Anyline; Berlin (MD); On-site; USD 100,000 - 130,000; Full time

Job summary

Anyline is seeking a Lead Data Engineer for its Berlin office, responsible for building and managing the data infrastructure essential for the company's AI transformation. The successful candidate will create accessible and unified data layers, define and track key performance indicators for AI usage, and collaborate closely with various stakeholders. Ideal applicants will have expertise in Python, SQL, and ETL tools, alongside experience in AI-related data engineering. This role is pivotal in ensuring data governance and compliance across the organization.

Qualifications

• Experience designing data layers for AI/LLM applications.
• Proficiency in Python and SQL for data manipulation.
• Knowledge of dimensional modeling and data warehouse technologies.

Responsibilities

• Build and own the data infrastructure for AI transformation.
• Create self-serve access layers for data.
• Define KPIs and dashboards to track AI impact.

Skills

Python

SQL

ETL/ELT tools

MLOps

Data Governance

Job description

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 Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.

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. 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.

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 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.

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 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.