Senior Data Engineer

GROPYUS is a technology-based construction company focused on building multi-story residential buildings. Thanks to its prefabricated building system with various design options, industrial offsite construction, and fully digitalized processes, the company manufactures aspirational, sustainable, and affordable homes using timber construction methods. GROPYUS is using scalable construction and manufacturing solutions to tap into a future market, boost Europe's strength in innovation, while also playing a substantial role in improving sustainability.

We are growing our Data Platform Team within the Gropyus Tech department. Our Platform team is responsible for our internal platform, the Gropyus Data Fabric.

Our team interacts with experts from various domains such as Digital Building Planning and Automation, Product Operations, Sustainability, AI, IoT, construction engineers, building architects, logistics experts, software engineering; solving complex challenges pertaining to end-to-end process for planning, building, and operating a building.

What You Will Be Doing:

As part of the Data Platform organization, you will:

What You Bring:

Optional Experience:

• Design, build, and maintain core data platform components, including ingestion frameworks, transformation pipelines, and data storage layers
• Own and improve data reliability through monitoring, alerting, SLAs, and data quality checks
• Collaborate with domain experts and software engineers to understand data needs and deliver high-quality datasets.
• Lead strategic initiatives to modernize or scale our data ecosystem (including query optimization, schema design, analytics, etc)
• Mentor and guide team members to elevate engineering rigor and technical capability
• Experience working with a tech stack similar to:
• Programming languages like Python or Kotlin.
• Databases like Postgres, BigQuery, Spark, Graph DB
• Tools like: Kubernetes, Docker, Terraform, Dagster, DBT
• Cloud Storage Platforms
• You have strong problem-solving and analytical skills and the ability to break down complex tasks for operations including working with stakeholders, adapting to dynamic input, and leading implementation projects
• You have experience identifying and resolving issues related to data discrepancies and inconsistencies and creating validation and testing for prevention and handling
• You have experience in building, operating, and scaling data intensive reactive processing pipelines from end to end including ingestion, storage, orchestration, transformation, enrichment, and analytics
• Some knowledge about semantic web technologies like RDF and OWL