IONOS

Analytics Engineer

• Design and operate reliable data pipelines using Python and SQL to ingest and transform interaction data from voice and text channels.
• Manage the data lifecycle within our core databases: PostgreSQL for structured application data and Elasticsearch for search and retrieval.
• Build and maintain scalable dbt projects to transform raw logs into high-quality, governed data models.
• Act as a Data Analyst expert: collaborate with stakeholders to define key performance indicators (KPIs) like resolution rates, intent accuracy, and cost-per-interaction.
• Build and maintain business-facing dashboards in Looker and internal data applications in Streamlit.
• Translate complex technical traces into actionable insights for the product and business teams.
• Own the "Retrieval" layer: optimize how data is indexed and queried in Elasticsearch to improve AI response context.
• Develop the pipelines that manage chunking, metadata tagging, and context window optimization.
• Instrument our data stack and AI services with Prometheus and Grafana to monitor system health, latency, and pipeline reliability.
• Ensure proactive alerting for data quality issues or service degradations.

Data & Analytics Engineer – AI Platform

Product Designer

• Work closely with Product Owners to understand goals and shape product features;
• Support the definition of customer journeys, user flows, wireframes and prototypes (low- and high-fidelity);
• Contribute to design specifications and help translate them into working software together with developers;
• Create and maintain Figma screens and components;
• Maintain and improve the team’s design system and style guide;
• Participate in user research preparation and contribute to research activities;
• Iterate on design decisions based on data and user behavior;
• Collaborate with cross-functional teams (developers, QAs, designers) across locations;
• Take part in team ceremonies (Scrum meetings, sprints ceremonies);
• Gradually grow into a point of contact for design-related topics within the team.

UX Working Student – Product & Design

Backend Engineer

• Design, develop, and maintain data pipelines and ETL processes using MS SQL Server, and Python, ensuring reliable data movement from source systems to the data warehouse and analytical layers.
• Build and operate real-time and near-real-time data ingestion pipelines using Apache Kafka — designing topics, building producers and consumers, and managing stream processing workflows.
• Develop and optimize stored procedures, views, and data transformation logic for both backend processing and frontend consumption (SSAS, Power BI).
• Write and maintain Python-based data services and integrations, leveraging libraries such as sqlalchemy, pyodbc, confluent_kafka, json, and FastAPI to connect, transform, and expose data across systems.
• Perform requirements analysis and effort estimation within projects and implement solutions as part of an international, cross-functional team.
• Collaborate closely with BI analysts and architects to translate business requirements into robust, scalable data solutions.
• Support Business Analysts with ad-hoc analyses on large data volumes, complex data models, and data extraction from operational systems.
• Design, code, test, debug, document, and support all types of data flows and transformation procedures consistent with established specifications and business requirements to deliver maximum business value.
• Support, enhance, and modify existing applications, pipelines, and codebases.

Data Engineer, Python, Kafka

Business Intelligence Analyst

• Design, implement, and maintain scalable data pipelines and workflows using Azure Databricks and the broader Azure data platform (Data Factory, Data Lake Storage, Azure SQL), ensuring reliability, performance, and cost efficiency
• Develop and optimize data transformation logic using PySpark and SQL within Databricks, handling large-scale datasets across batch and streaming workloads
• Build and maintain data movement procedures, views, and flows for both frontend and backend systems, leveraging MS SQL Server, SSAS, Power BI, and Azure cloud services
• Collaborate closely with BI analysts and architects to translate business requirements into robust data engineering solutions; implement new ideas and improvements driven by that collaboration
• Perform requirement analyses and effort estimations within projects and deliver solutions as part of an international team
• Support Business Analysts with ad-hoc analyses on large data volumes, complex data models, and data extraction from operational systems
• Design, code, test, debug, document, and support all types of data flows and transformation procedures consistent with established specifications and business requirements to deliver maximum business value
• Support, enhance, and modify existing applications, codebases, and data pipelines

Data & Analytics Engineer – AI Platform

UX Working Student – Product & Design

Data Engineer, Python, Kafka

Data Engineer, Databricks, Access & Business Intelligence