About Us:
CloudGeometry is a leading Silicon Valley-based cloud-native system integrator with deep expertise in AWS and the CNCF technology stack. We partner with industry leaders like AWS, Google and Databricks to deliver solutions across all layers of the modern technology stack, from generative UI to Kubernetes-powered MLOps workloads. Our distributed team of top technology experts from the US, Europe, and LATAM collaborates on innovative commercial and open-source projects. Our commitment to innovation and excellence makes us a trusted partner for leading technology companies and VC-funded startups. By pushing the boundaries of what's possible, we help our clients stay ahead in a rapidly evolving technological landscape
Cloudgeometry Engineering Profile:
We are seeking experienced senior software engineers who possess a deep passion for technology and an eagerness to tackle complex technical challenges. You have a strong interest in leveraging AI and cutting-edge methodologies to drive efficiency and precision in your work. A strong commitment to the organization's growth and the advancement of its internal ventures is critical. You care about your project, but also about CloudGeometry communities and their development. Sharing best practices with engineering communities across projects is paramount to you. You must demonstrate a commitment to continuous learning, allocating time to acquire new skills and obtain certifications to validate your expertise and experience.
Project Description:
We’re looking for a Data Engineer to join a high-impact team building robust, cloud-native data infrastructure that supports machine learning and analytics workflows at scale. This role is ideal for someone who has hands-on experience with Databricks, enjoys building efficient and scalable data pipelines, and is eager to grow their platform skills in a dynamic, multi-cloud environment.
You will be part of a cross-functional team including platform engineers, DevOps, and data scientists, collaborating on ingestion, transformation, orchestration, and data reliability for production-grade pipelines.
Responsibilities:
* Build and maintain scalable ETL/ELT pipelines on Databricks using Spark, Delta Lake, and Python.
* Develop orchestration logic using tools such as AWS Step Functions, Lambda, or Databricks Workflows.
* Contribute to medallion architecture layers (Bronze, Silver, Gold) for structured data processing.
* Collaborate on infrastructure provisioning and pipeline automation using Terraform and GitHub Actions.
* Troubleshoot Spark job performance and help ensure reliable, efficient data pipelines.
* Support cross-functional teams (data scientists, ML engineers) by delivering curated, production-ready data.
Required Skills:
* 3–6 years of experience in data engineering or data platform roles.
* Solid experience with Databricks and Delta Lake, including job and cluster setup.
* Strong in PySpark, SQL, and scripting for data transformation.
* Familiarity with AWS services: S3, Lambda, Step Functions, IAM, CloudWatch.
* Exposure to CI/CD practices and infrastructure automation using Terraform.
Nice-to-Have
* Familiarity with Unity Catalog, MLflow, or other MLOps tools.
* Experience designing pipelines in multi-tenant or highly-regulated environments.
Benefits:
* Remote anywhere
* Coworking space financial coverage
* Flexible working hours
* B2B with multiple benefits
* Paid days off annually
* Workspace program: $2500 for work equipment of your choice.
* English language lessons on all levels
* Performance financial incentives for the people who demonstrate interest in the company’s development.
* Paid courses and certifications: example AWS, CKA, ML certifications
* Participation at international conferences: like CNCF Summits, Kubecon, others