Solvits Solutions

About the job:

We are 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.

‍

Responsibilities:

• 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 Spark on Kubernetes, Kafka, and AWS services.
• 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:
 

• 8+ years of hands-on experience working with large-scale data systems in production environments.
• Proven experience designing, deploying, and integrating big data frameworks - PySpark, Kafka, Databricks. 
• Strong expertise in Python and SQL, with experience building and optimizing batch and streaming data pipelines.
• Experience with AWS cloud services and Linux-based environments.
• Background in building ETL/ELT pipelines and orchestrating workflows end-to-end.
  Proven experience designing, deploying, and operating data infrastructure / data platforms.
• Mandatory hands-on experience with Apache Spark in production environments. 
• Mandatory experience running Spark on Kubernetes.
• Mandatory hands-on experience with Apache Kafka, including Kafka connectors.
• Understanding of event-driven and domain-driven design principles in modern data architectures.
• Familiarity with infrastructure-as-code tools (e.g., Terraform) — advantage.
• Experience supporting machine learning or algorithmic applications — advantage.
• BSc or higher in Computer Science, Engineering, Mathematics, or another quantitative field.