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Staff Data Engineer – Internal Platform(m/w/x)
Building internal data infrastructure for agentic AI, including a self-serve access layer for AI agents. Experience designing AI/LLM data layers required. Databricks workspace management, Airbyte pipeline configuration.
Requirements
- Experience designing AI/LLM data layers
- Proficiency in Python, SQL, ETL/ELT tools, MLOps
- Knowledge of dimensional modeling
- Knowledge of modern data warehouse technologies
- Ability to execute complex requirements
- Ability to resolve performance issues
- Ability to articulate technical concepts to non-engineers
- Ability to make data architecture decisions understandable
- Passion for data engineering innovation
- Ability to define Al adoption KPIs
- Understanding of AI data consumption
- Understanding of data optimisation for AI
Tasks
- Build and own data infrastructure for internal AI transformation
- Create single, self-serve access layer for AI agents and teams
- Define KPIs and dashboards for AI adoption and impact tracking
- Configure and manage internal Databricks workspace end-to-end
- Build and maintain Airbyte pipelines for data ingestion
- Implement architecture for transforming raw data into analysis-ready datasets
- Partner with AI Transformation Team for data enablement
- Define and build KPIs and dashboards for AI usage and impact
- Manage data classification, access policies, and compliance
- Monitor data pipelines for governance and compliance
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- ETL/ELT tools
- MLOps
- AI
- LLM
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Staff Data Engineer – Internal Platform(m/w/x)
Building internal data infrastructure for agentic AI, including a self-serve access layer for AI agents. Experience designing AI/LLM data layers required. Databricks workspace management, Airbyte pipeline configuration.
Requirements
- Experience designing AI/LLM data layers
- Proficiency in Python, SQL, ETL/ELT tools, MLOps
- Knowledge of dimensional modeling
- Knowledge of modern data warehouse technologies
- Ability to execute complex requirements
- Ability to resolve performance issues
- Ability to articulate technical concepts to non-engineers
- Ability to make data architecture decisions understandable
- Passion for data engineering innovation
- Ability to define Al adoption KPIs
- Understanding of AI data consumption
- Understanding of data optimisation for AI
Tasks
- Build and own data infrastructure for internal AI transformation
- Create single, self-serve access layer for AI agents and teams
- Define KPIs and dashboards for AI adoption and impact tracking
- Configure and manage internal Databricks workspace end-to-end
- Build and maintain Airbyte pipelines for data ingestion
- Implement architecture for transforming raw data into analysis-ready datasets
- Partner with AI Transformation Team for data enablement
- Define and build KPIs and dashboards for AI usage and impact
- Manage data classification, access policies, and compliance
- Monitor data pipelines for governance and compliance
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- ETL/ELT tools
- MLOps
- AI
- LLM
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Parloa
Industry
IT
Description
Parloa is a fast-growing startup in Generative AI and customer service, offering a voice-first GenAI platform for contact centers.
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