Altamira is a software development outsourcing company. We provide solutions that make a tangible impact on our client’s growth and productivity. With domain knowledge across product and technology development, we aim to provide cost-efficient solutions without compromising quality. We are driven to deliver the best, every single time.
Altamira service delivery teams currently span Slovakia, Ukraine, and the Middle East, and we have ambitions to expand our footprint to meet the growing demand across Europe and into our primary growth markets in the UK and the US. In terms of industry verticals, we are focused on EdTech, Fintech, eCommerce, and Pharma.
We are looking for a highly technical Senior Databricks Engineer to take ownership of optimizing and productionizing Databricks workloads created by data scientists. You will work independently, focusing on Spark performance tuning, data partitioning, CI/CD automation, and MLOps design, ensuring that ML pipelines are robust, scalable, and production-ready.
Our client is one of the largest financial institutions in Central and Eastern Europe. Their data & ML platform is built on Azure Databricks, and they are looking for an expert who can bring their ML workloads to the next level in terms of performance, reliability, and operational excellence.
Optimize and productionize Databricks notebooks and jobs developed by data scientists
Tune Spark performance (cluster configuration, caching, data partitioning, shuffle optimization)
Design and implement MLOps frameworks for model training, deployment, and monitoring
Set up and maintain CI/CD pipelines for Databricks using Jenkins or Azure DevOps
Work with Databricks Asset Bundles to manage code, configs, and deployments
Configure and fine-tune clusters, jobs, and workflows for cost and performance efficiency
Integrate with Azure services: ADLS, Key Vault, AAD, and others
Own technical delivery, progress tracking, and quality – working largely independently, with a strong focus on execution
Strong hands-on experience with Azure Databricks (DBX): clusters, jobs, notebooks, asset bundles
Deep knowledge of Apache Spark: performance tuning, data partitioning, optimization strategies
Experience designing and implementing MLOps frameworks in a production environment
Proven experience with CI/CD automation (Jenkins and/or Azure DevOps pipelines)
Familiarity with Azure cloud components: ADLS, Key Vault, AAD
Solid Python skills for Databricks notebooks
Experience with Git and branching strategies for data/ML projects
Strong ownership mindset: ability to work independently, drive delivery, and communicate progress clearly
Fluent English (spoken and written)
Nice to have:
Terraform for infrastructure-as-code on Azure
Experience in the financial services domain
German language skills (a plus, but not required)
If you enjoy deep technical work, love making Spark workloads fly, and want to have a visible impact on a large-scale financial data platform, this role is for you.
Our transparent recruitment journey usually takes up to 2 weeks and includes a few stages:
We do believe that the success of altamira.ai is impossible without the success of our Talents and the success of our Clients!
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