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Senior Data Engineer with Databricks

At Grow2FIT · Bratislava, Slovakia

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“Bratislava, Slovakia”

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First seen by us
15 October 2026
Last checked
11 hours ago

Job description

From Grow2FIT’s job post, as they wrote it.

Key Responsibilities

* Design scalable, secure, and high-performance data platforms using Databricks and Lakehouse architecture.
* Lead end-to-end architecture design for data lakes, lakehouses, and data warehouses.
* Define data architecture standards, governance principles, and best practices.
* Design batch and streaming data processing solutions.
* Translate business requirements into technical architectures and implementation roadmaps.

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* Provide technical leadership and architectural guidance to data engineering teams.
* Conduct architecture reviews, technical assessments, and client workshops.
* Advise clients on data platform modernization, performance optimization, security, and cost efficiency.

Key Requirements

* 5+ years of experience designing and implementing cloud-based data platforms, ideally in a Data Architect or Senior Data Engineer role.
* Strong hands-on experience with Databricks, Apache Spark, Delta Lake, and Lakehouse architecture.
* Strong SQL and PySpark skills, including performance optimization.
* Experience with Unity Catalog, Databricks Workflows, and Delta Live Tables / Lakeflow Spark Declarative Pipelines.
* Solid understanding of data modeling (Kimball, Inmon, Medallion Architecture) and ETL/ELT principles.
* Experience designing batch and streaming data pipelines.
* Experience with at least one major cloud platform (Azure, AWS, or GCP).
* Knowledge of data governance, security, CI/CD, Infrastructure as Code, and DevOps practices.
* Strong communication skills and the ability to lead technical discussions with clients and delivery teams.

Nice to Have

* Databricks certifications.
* Experience with Azure Databricks and Azure data services.
* Experience with Apache Kafka and Spark Structured Streaming.
* Cloud migration and data platform modernization experience.
* Familiarity with MLflow and AI/ML workloads.
* Previous experience in client-facing consulting roles.

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