Senior Azure Databricks Engineer

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.

About the Client

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.

What you will do

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Optimize and productionize Databricks notebooks and jobs developed by data scientists

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Tune Spark performance (cluster configuration, caching, data partitioning, shuffle optimization)

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Design and implement MLOps frameworks for model training, deployment, and monitoring

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Set up and maintain CI/CD pipelines for Databricks using Jenkins or Azure DevOps

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Work with Databricks Asset Bundles to manage code, configs, and deployments

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Configure and fine-tune clusters, jobs, and workflows for cost and performance efficiency

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Integrate with Azure services: ADLS, Key Vault, AAD, and others

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Own technical delivery, progress tracking, and quality – working largely independently, with a strong focus on execution

Requirement:

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Strong hands-on experience with Azure Databricks (DBX): clusters, jobs, notebooks, asset bundles

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Deep knowledge of Apache Spark: performance tuning, data partitioning, optimization strategies

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Experience designing and implementing MLOps frameworks in a production environment

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Proven experience with CI/CD automation (Jenkins and/or Azure DevOps pipelines)

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Familiarity with Azure cloud components: ADLS, Key Vault, AAD

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Solid Python skills for Databricks notebooks

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Experience with Git and branching strategies for data/ML projects

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Strong ownership mindset: ability to work independently, drive delivery, and communicate progress clearly

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Fluent English (spoken and written)

Nice to have:

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Terraform for infrastructure-as-code on Azure

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Experience in the financial services domain

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:

• Recruiting Interview -> 30-45 min

• Technical Interview -> 1-1,5h

• Client Interview (optional) -> up to 1h

• Pre-Offer Call -> 15min

• Reference Check

• Offer

We offer:

• Competitive salary, room for development and growth.

• Possibility to work in the Bratislava and Kyiv offices or fully remotely.

• Loyal management, interesting tasks, constant support.

• Medical insurance (optional).

• English courses.

• Technical equipment providing.

• Paid vacations 20 workdays, paid sick leave, regular salary reviews;

• Flexible schedule and ability to manage your working hours;

• Support your personal growth and skills upgrading.

• The great environment inside the team, support of initiatives, and ability to contribute to the common goal.

We do believe that the success of altamira.ai is impossible without the success of our Talents and the success of our Clients!