Location: Tel Aviv, Israel
Versatile is an innovative AI-driven construction intelligence startup, committed to transforming the construction industry with cutting-edge technology. Our mission is to enhance the efficiency, safety, and productivity of construction projects through intelligent solutions.
We’re hiring a hands-on Senior Data Engineer who wants to build data products that move the needle in the physical world. Your work will help construction professionals make better, data-backed decisions every day. You’ll be part of a high-performing engineering team based in Tel Aviv.
What you will be doing:
- Lead the design, development, and ownership of scalable data pipelines (ETL/ELT) that power analytics, product features, and downstream consumption.
- Collaborate closely with Product, Data Science, Data Analytics, and full-stack/platform teams to deliver data solutions that serve product and business needs.
- Build and optimize data workflows using Databricks, Spark (PySpark, SQL), Kafka, and AWS-based tooling.
- Implement and manage data architectures that support both real-time and batch processing, including streaming, storage, and processing layers.
- Develop, integrate, and maintain data connectors and ingestion pipelines from multiple sources.
- Manage the deployment, scaling, and performance of data infrastructure and clusters, including Databricks, Kafka, and AWS services.
- Use Terraform (and similar tools) to manage infrastructure-as-code for data platforms.
- Model and prepare data for analytics, BI, and product-facing use cases, ensuring high performance and reliability.
Requirements:
- 5+ years of hands-on experience working with large-scale data systems in production environments.
- Proven experience designing, deploying, and integrating big data frameworks such as PySpark, Kafka, Databricks, or equivalent cloud-based data platforms.
- Strong expertise in Python and SQL, with experience building and optimizing data processing workflows (batch and/or streaming).
- Experience with AWS cloud services and Linux-based environments.
- Background in building ETL/ELT pipelines and orchestrating workflows end-to-end.
- Understanding of event-driven and domain-driven design principles in modern data architectures.
- Experience preparing data for BI, analytics, and consumption by product teams or platforms.
- Familiarity with infrastructure-as-code tools (e.g., Terraform) — advantage.
- Experience with parquet, delta table format, Debezium, or AWS-native data solutions — advantage.
- Experience in data modeling, data analysis, or supporting visualization/analytics teams — advantage.
- Familiarity with data visualization tools or creating dashboards — advantage.
- Experience supporting machine learning or algorithmic applications — nice to have.
- BSc or higher in Computer Science, Engineering, Mathematics, or another quantitative field.