Role overview
Atlas is a data engineering team that owns Explorium's core data products end-to-end - from ingestion and enrichment through transformation, quality, and serving. We build and operate the pipelines, data models, and platform services that power the product.
We work closely with our customers and external data providers to assess, integrate, and enhance third-party data assets.
The Role
We're looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isn't a pure infrastructure role - you'll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. You'll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
What we're looking for
- Experience with GenAI and LLM applications — particularly extracting structure from unstructured data at scale
- Experience working with external data sources and vendors
- Familiarity with Unity Catalog and data governance at scale
- Familiarity with Terraform or similar infrastructure-as-code tools
- Experience with cost optimization on Databricks (DBU analysis, cluster policies)
- Familiarity with cloud-native platforms (AWS preferred)
- BSc/BA in Computer Science, Engineering, or a related technical field — or graduation from a top-tier IDF tech unit