Technology, Information and Internet

Aroundhome

201-500

<h2>Responsibilities</h2>
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 &amp; 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.
​
<ul>
<li>Data Modeling &amp; Transformation: <ul>
<li>Design necessary data models and transformations to curate raw data. </li>
<li>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.</li>
</ul>
</li>
<li>Data Platform Architecture: <ul>
<li>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. </li>
<li>Optimize ETL/ELT pipelines using tools like DBT, Spark, or Airflow, bridging upstream (e.g. Debezium, MSK) and downstream processes. </li>
<li>Evaluate and integrate new technologies to support hybrid monolith-microservices architecture and ML and AI enablement. </li>
<li>Ensure seamless migrations and minimal disruptions during platform evolution.</li>
</ul>
</li>
<li>Real-Time Data Integration: Build and optimize real-time data pipelines using Kafka, Spark, and Delta Live Tables.</li>
<li>Data Governance &amp; Quality: <ul>
<li>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. </li>
<li>Ensure the existence of, or adaptation to, full Data Life Cycle Management (DLCM) and end-to-end testing.</li>
</ul>
</li>
<li>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.</li>
<li>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.</li>
<li>Stakeholder Collaboration: Collaborate with Product Analytics, domain teams, and business to deliver data solutions that drive value and are aligned with business needs.</li>
</ul>
<h2>Skills</h2>
<ul>
<li>Master's degree in Computer Science, Data Engineering, or related field (or equivalent experience)</li>
<li>10+ years of experience in data engineering, with 5+ years in senior roles focused on modern architectures.</li>
<li>Excellent communication and collaboration skills, the ability to drive change and influence stakeholders, and a passion for mentoring, coaching, and sharing knowledge</li>
<li>Proven expertise in designing, developing &amp; maintaining data lakehouses/DWH (e.g., Databricks Delta Lake, Snowflake) and transformations (e.g., DBT, SQL/Python/Spark).</li>
<li>Strong experience with cloud platforms such as AWS services (S3, Athena, MSK/Kafka, Terraform) and real-time streaming (e.g., Kafka, Spark Structured Streaming, Flink).</li>
<li>Hands-on knowledge of data governance tools (e.g., Unity Catalog, Collibra) for lineage, quality, catalogs, and SSOT.</li>
<li>Familiarity in AI/ML pipelines and MLOps (e.g., MLflow, feature stores) and complex system integration within modern data technologies.</li>
<li>Proficiency in CI/CD for data, and tools like Git, Airflow, or dbt Cloud.</li>
<li>Experience with large-scale data modeling (DataVault, dimensional, schema-on-read) and optimizing for self-service analytics.</li>
</ul>
<h2>What we offer</h2>
Hybrid Work // Stay flexible: Decide freely whether you want to work from our office in Berlin, from home throughout Germany, or fully remote from Portugal. Additionally, we offer you the possibility to work up to 30 days per year from selected EU countries. 
Room to grow // Stay curious: In regular/annual feedback meetings, you design your own personal development path together with your team lead. In addition, we offer monthly Tech Talks, an annual training budget, as well as great workshops to seek new input and specific training for your personal development.
Mental &amp; physical health // Stay healthy &amp; active: We care about your well-being and support your health with a discounted membership at Urban Sports Club. In addition, our cooperation partner “Fürstenberg Institute” is available to you and your family members with advice and support when it comes to mental health &amp; coaching.
Taking responsibility // We #care: We care for our planet and the people who are living on it. To make our world a little bit better, our ESG Team (Environmental, Social &amp; Governance) promotes our awareness for environmentally friendly behavior. In addition, we work with JobRad, offer a discounted BVG ticket, and actively support social projects in Berlin at our annual Social Day to give something back.
Teamspirit // Stay connected: What drives us is our sense of community. That's why we celebrate our Company Day once a month in our office at Potsdamer Platz, where everyone gets together in person. In addition to a comprehensive update of our C-Board, the main focus is on togetherness and the exchange of ideas over lunch and dinner together.

(Senior) Data Engineer (Modern Data Platform & AI) (all genders) | Berlin, hybrid or remote

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