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Senior Databricks Data Engineer

https://www.inetum.com Logo

Inetum

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Location:
Romania , Bucharest

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Category:
IT - Software Development

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Contract Type:
Employment contract

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Salary:

Not provided
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Job Description:

To develop, implement, and optimize complex Data Warehouse (DWH) and Data Lakehouse solutions using the Databricks platform to ensure a scalable, high-performance, and governed data foundation for analytics, reporting, and Machine Learning.

Job Responsibility:

  • Design and implement robust, scalable, and high-performance ETL/ELT data pipelines using PySpark/Scala and Databricks SQL on the Databricks platform
  • expertise in implementing and optimizing the Medallion architecture (Bronze, Silver, Gold) using Delta Lake
  • design and implement real-time/near-real-time data processing solutions using Spark Structured Streaming and Delta Live Tables (DLT)
  • implement Unity Catalog for centralized data governance, fine-grained security (row/column-level security), and data lineage
  • develop and manage complex workflows using Databricks Workflows (Jobs) or external tools (Azure Data Factory, Airflow) to automate pipelines
  • integrate Databricks pipelines into CI/CD processes using tools like Git, Databricks Repos, and Bundles
  • work closely with Data Scientists, Analysts, and Architects to deliver optimal technical solutions
  • provide technical guidance and mentorship to junior developers.

Requirements:

  • Proven, expert-level experience with the entire Databricks ecosystem (Workspace, Cluster Management, Notebooks, Databricks SQL)
  • in-depth knowledge of Spark architecture (RDD, DataFrames, Spark SQL) and advanced optimization techniques
  • expertise in implementing and managing Delta Lake (ACID properties, Time Travel, Merge, Optimize, Vacuum)
  • advanced/expert-level proficiency in Python (with PySpark) and/or Scala (with Spark)
  • advanced/expert-level skills in SQL and Data Modeling (Dimensional, 3NF, Data Vault)
  • solid experience with a major Cloud platform (AWS, Azure, or GCP), especially with storage services (S3, ADLS Gen2, GCS) and networking
  • bachelor’s degree in Computer Science, Engineering, Mathematics, or a relevant technical field
  • minimum of 5+ years of experience in Data Engineering, with at least 3+ years of experience working with Databricks and Spark at scale.

Nice to have:

  • Hands-on experience with implementing and managing Unity Catalog
  • experience with Delta Live Tables (DLT) and Databricks Workflows
  • understanding of basic MLOps concepts and experience with MLflow to facilitate integration with Data Science teams
  • experience with Terraform or equivalent tools for Infrastructure as Code (IaC)
  • Databricks certifications (e.g., Databricks Certified Data Engineer Professional).
What we offer:
  • Full access to foreign language learning platform
  • personalized access to tech learning platforms
  • tailored workshops and trainings to sustain your growth
  • medical insurance
  • meal tickets
  • monthly budget to allocate on flexible benefit platform
  • access to 7 Card services
  • wellbeing activities and gatherings.

Additional Information:

Job Posted:
November 21, 2025

Employment Type:
Fulltime
Work Type:
Hybrid work
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