Big Data Engineer (Databricks)

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Big Data Engineer (Databricks)

2025.06.05.

Summary

Bucharest, ROU

Remote

Senior

Introduction

SwiconGroup is one of the leading members of the IT arena for almost a decade, since 2017 present also in Romania. Our wide range of services and highly trained professionals give us the opportunity to shape our solutions to fully meet the ideas and wishes of our clients. We are proud to have leading banks, insurance and telecommunication companies, as well as large FMCG corporations and SSCs amongst our highly prestigious partners.

Description

Develop a comprehensive technical plan for the migration, including data ingestion, transformation, storage, and access control within Azures Data Factory and data lake.Design and implement scalable and efficient data pipelines to ensure smooth data movement from multiple sources using Azure Databricks.Develop scalable and reusable frameworks for data ingestion.Ensure data quality and integrity throughout the data pipeline, implementing robust data validation and cleansing mechanisms.Work with event-based and streaming technologies to ingest and process data.Provide technical guidance and support to the team, resolving technical challenges or issues during the migration and post-migration phases.Stay current with advancements in cloud computing, data engineering, and analytics technologies, recommending best practices and industry standards for implementing data lake solutions.

Tasks

• Developing and managing scalable data pipelines/data workflows using Databricks for building

AI/ML solutions.

• Developing integrated software solutions for AI/ML models.

• Developing and maintaining scalable ML pipelines.

• Works with CI/CD teams for seamless model deployment.

• Implement end-to-end (E2E) AI solutions within Databricks and Cloud environments.

• Apply MLOps practices for effective model lifecycle management, including the use of CI/CD to

automate model development and deployment workflows.

xperience with Databricks.

Expectations

  • 5 to 7 years of IT experience.
  • Minimum of 2 years of experience working with Azure Databricks.
  • Expertise in Data Modeling and Source System Analysis.
  • Proficiency with PySpark.
  • Mastery of SQL.
  • Knowledge of Azure components: Azure Data Factory, Azure Data Lake, Azure SQL DW, and Azure SQL.
  • Experience with Python programming for data engineering purposes.
  • Ability to conduct data profiling, cataloging, and mapping for technical design and construction of technical data flows.
  • Experience with data visualization and exploration tools.

Employer's offer


  • Flexible and dynamic work environment involving teams spread across different global locations;
  • Communities with shared interests and identities, all working together to advance diversity, equity and inclusion within the workplace and society;
  •  Do you want to learn more? You will have access to various training programs and platforms
  • Attractive benefits package (meal tickets, medical services, Benefit online, Employee Share Option Plan).
  • Friendly and welcoming work environment with an international working atmosphere where you can practice and learn new language skills with a diverse mix of colleagues and clients.
  • A dynamic work environment with a culture that is open, innovative and performance orientated.

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Big Data Engineer (Databricks)

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I’ve grown a lot professionally in my time here, too. My tasks and my responsibilities have kept widening, I’ve been able to take on more complex challenges, and I’ve also had the chance to support and mentor others. On the IT side I’ve been given opportunities that made a real difference to where I am professionally, so on the whole I see SWICON as a supportive place that gives you genuine room to grow.”

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Trusted by enterprise leaders across the world

ROU Bucharest remote senior SwiconGroup is one of the leading members of the IT arena for almost a decade, since 2017 present also in Romania. Our wide range of services and highly trained professionals give us the opportunity to shape our solutions to fully meet the ideas and wishes of our clients. We are proud to have leading banks, insurance and telecommunication companies, as well as large FMCG corporations and SSCs amongst our highly prestigious partners. Develop a comprehensive technical plan for the migration, including data ingestion, transformation, storage, and access control within Azures Data Factory and data lake.Design and implement scalable and efficient data pipelines to ensure smooth data movement from multiple sources using Azure Databricks.Develop scalable and reusable frameworks for data ingestion.Ensure data quality and integrity throughout the data pipeline, implementing robust data validation and cleansing mechanisms.Work with event-based and streaming technologies to ingest and process data.Provide technical guidance and support to the team, resolving technical challenges or issues during the migration and post-migration phases.Stay current with advancements in cloud computing, data engineering, and analytics technologies, recommending best practices and industry standards for implementing data lake solutions. • Developing and managing scalable data pipelines/data workflows using Databricks for buildingAI/ML solutions.• Developing integrated software solutions for AI/ML models.• Developing and maintaining scalable ML pipelines.• Works with CI/CD teams for seamless model deployment.• Implement end-to-end (E2E) AI solutions within Databricks and Cloud environments.• Apply MLOps practices for effective model lifecycle management, including the use of CI/CD toautomate model development and deployment workflows.xperience with Databricks. 5 to 7 years of IT experience.Minimum of 2 years of experience working with Azure Databricks.Expertise in Data Modeling and Source System Analysis.Proficiency with PySpark.Mastery of SQL.Knowledge of Azure components: Azure Data Factory, Azure Data Lake, Azure SQL DW, and Azure SQL.Experience with Python programming for data engineering purposes.Ability to conduct data profiling, cataloging, and mapping for technical design and construction of technical data flows.Experience with data visualization and exploration tools. Flexible and dynamic work environment involving teams spread across different global locations; Communities with shared interests and identities, all working together to advance diversity, equity and inclusion within the workplace and society; Do you want to learn more? You will have access to various training programs and platformsAttractive benefits package (meal tickets, medical services, Benefit online, Employee Share Option Plan).Friendly and welcoming work environment with an international working atmosphere where you can practice and learn new language skills with a diverse mix of colleagues and clients.A dynamic work environment with a culture that is open, innovative and performance orientated.