Responsibilities
With a mission to empower 15.6 million house owners across Germany and the broader DACH region, we at Aroundhome are building a platform where every strategic decision is powered by data. We're a team of around 250 people, and to accelerate our journey, we're looking for an experienced Senior Data Engineer (Modern Data Platform & AI) to contribute in shaping our data foundation together with our Data Engineers.
You will report to the Data Platform Team Lead and work closely with different stakeholders to ensure a reliable, scalable, and accessible data platform for the whole company. Touchpoints with other functional areas include Product, Marketing, Finance and Product Analytics.
- Design necessary data models and transformations to curate raw data.
- Develop, optimize and maintain existing data models, pipelines, and transformations to support analytics, reporting, and AI use cases such as but not limited to curating, transforming, annotating and modeling data.
- Architect and contribute in implementing a scalable, modern data platform, including data lakehouse or warehouse, to support real-time/near-real-time data flows from Kafka to downstream consumers.
- Optimize ETL/ELT pipelines using tools like DBT, Spark, or Airflow, bridging upstream (e.g. Debezium, MSK) and downstream processes.
- Evaluate and integrate new technologies to support hybrid monolith-microservices architecture and ML and AI enablement.
- Ensure seamless migrations and minimal disruptions during platform evolution.
- Real-Time Data Integration: Build and optimize real-time data pipelines using Kafka, Spark, and Delta Live Tables.
- Support the team lead in establishing and enforcing data governance frameworks, including data lineage, quality standards, catalogue, metadata management, SSOT for business glossaries/CBC terms, and policies to ensure reliable reporting.
- Ensure the existence of, or adaptation to, full Data Life Cycle Management (DLCM) and end-to-end testing.
- AI/ML Enablement: Collaborate with the team to integrate AI/ML capabilities, such as feature engineering and model serving, to accelerate data products for market penetration and operational efficiency, as well as operationalizing ML models and integrate AI into business processes.
- Knowledge Sharing: Mentor the team on best practices, modern tools (e.g., Databricks, Snowflake, AI adaptation and integrations like Cursor/CodeRabbit), and cloud-native scalability. And last but not least foster a culture of innovation and continuous improvement.
- Stakeholder Collaboration: Collaborate with Product Analytics, domain teams, and business to deliver data solutions that drive value and are aligned with business needs.
Skills
- Master's degree in Computer Science, Data Engineering, or related field (or equivalent experience)