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Data Engineer on Cloud

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What you’ll work on

Full posting
  • Design, build and maintain batch and near real-time ETL pipelines into the cloud

  • Write clean, maintainable Python code following coding standards

  • Develop and optimise data transformation and modelling processes

  • Build and optimise data solutions using Google Cloud services

  • Debug and resolve complex issues in data pipelines

From the employer’s posting
Design, implement, and maintain fast, reliable ETL pipelines (both batch and near real-time)
Craft clean, efficient, and maintainable Python code following best practices and coding standards
Develop and optimize data transformation processes to deliver structured, actionable data to our consumers.
Utilize cloud services from Google Cloud Platform to build and optimize data solutions.
Employ advanced debugging tools and techniques to identify, troubleshoot, and resolve complex issues within data pipelines.

What you’ll bring

All qualifications

Core experience

  • Prior experience with Google Cloud Platform, including services like BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS, Cloud Composer (Airflow) is highly appreciated.
  • 24 days holiday, loyalty days, and bank holidays (including weekdays for weekend bank holidays).
  • Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.
Qualification wording
Cloud Proficiency: Experience with one or more cloud platforms (Google Cloud, AWS, or Azure) and a solid understanding of their data services. Prior experience with Google Cloud Platform, including services like BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS, Cloud Composer (Airflow) is highly appreciated.
24 days holiday, loyalty days, and bank holidays (including weekdays for weekend bank holidays).
Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.
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Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

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Deutsche Bank is hiring

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See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • AWS
  • Azure
  • BigQuery
  • Google Cloud Storage
  • Terraform
  • Airflow
  • GCP
Where the posting names them
- Develop Scalable ETL Pipelines: Design, implement, and maintain fast, reliable ETL pipelines (both batch and near real-time) that integrate diverse data sources into our cloud environment. - Write Quality Code: Craft clean, efficient, and maintainable Python code following best practices and coding standards; experience with Java is considered a bonus. - Data Transformation & Modeling: Develop and optimize data transformation processes to deliver structured, actionable data to our consumers. Experience with data warehousing is a plus.
Skills - Hands-On Data Engineering: 2.5 + years of experience building scalable data pipelines, with a strong focus on writing robust, maintainable Python code (Java is consider a plus). - Cloud Proficiency: Experience with one or more cloud platforms (Google Cloud, AWS, or Azure) and a solid understanding of their data services. Prior experience with Google Cloud Platform, including services like BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS, Cloud Composer (Airflow) is highly appreciated.
- Data Transformation: Familiarity with data modeling and ETL processes; direct experience with data warehousing is advantageous but not essential. - Software Development Practices: Experience with version control tools (e.g. Git / Bitbucket), CI/CD pipelines (e.g., GitHub Actions, TeamCity, Jenkins), and unit testing frameworks (such as Pytest/Unittest for Python or Junit for Java). - Debugging Skills: Demonstrated ability to troubleshoot and resolve complex technical issues.
- Hands-On Data Engineering: 2.5 + years of experience building scalable data pipelines, with a strong focus on writing robust, maintainable Python code (Java is consider a plus). - Cloud Proficiency: Experience with one or more cloud platforms (Google Cloud, AWS, or Azure) and a solid understanding of their data services. Prior experience with Google Cloud Platform, including services like BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS, Cloud Composer (Airflow) is highly appreciated. - Data Transformation: Familiarity with data modeling and ETL processes; direct experience with data warehousing is advantageous but not essential.
- Debugging Skills: Demonstrated ability to troubleshoot and resolve complex technical issues. - Bonus Skills: Familiar with any Infrastructure as Code tools (e.g. Terraform, Ansible, Chef), and hands-on experience with shell scripting. - Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.
As part of one of the internationally staffed, agile teams of the Private Bank – Data and Analytics domain, you will be part of the Global Data Platform subdomain. Focus is on the development and delivery of different solutions in the field of data warehousing, reporting and analytics for the Private Bank to ensure that necessary data is provided for operational and analytical purposes. The Global Data Platform is the new, strategic data platform of the Private Bank and uses the Google Cloud Platform as a basis. With Google as a close partner, we are following Deutsche Bank's cloud strategy with the aim of transferring a significant proportion of today's on-prem applications to the Google cloud platform or building new ones there. Responsabilities
- Data Transformation & Modeling: Develop and optimize data transformation processes to deliver structured, actionable data to our consumers. Experience with data warehousing is a plus. - Cloud Integration: Utilize cloud services from Google Cloud Platform to build and optimize data solutions. - Problem Solving: Employ advanced debugging tools and techniques to identify, troubleshoot, and resolve complex issues within data pipelines.

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Job description

View original posting ↗

Data Engineer on Cloud (f/m/x)
Job ID:R0455032 Full/Part-Time: Full-time Regular/Temporary: Regular Listed: 2026-11-02 Location: Bucharest

Position Overview

DB Global Technology is Deutsche Bank’s technology centre in Central and Eastern Europe. Since its set-up in 2013, Bucharest Technology Centre (BEX) has constantly proven its capacity to deliver global technology products and services, playing a dynamic role in the Bank’s technology transformation.


We have a robust, hands-on engineering culture dedicated to continuous learning, knowledge-sharing, technical skill development and networking. We are an essential part of the Bank’s technology platform and develop applications for many important business areas.


Area/ Team

As part of one of the internationally staffed, agile teams of the Private Bank – Data and Analytics domain, you will be part of the Global Data Platform subdomain. Focus is on the development and delivery of different solutions in the field of data warehousing, reporting and analytics for the Private Bank to ensure that necessary data is provided for operational and analytical purposes.


The Global Data Platform is the new, strategic data platform of the Private Bank and uses the Google Cloud Platform as a basis. With Google as a close partner, we are following Deutsche Bank's cloud strategy with the aim of transferring a significant proportion of today's on-prem applications to the Google cloud platform or building new ones there.


Responsabilities

  • Develop Scalable ETL Pipelines: Design, implement, and maintain fast, reliable ETL pipelines (both batch and near real-time) that integrate diverse data sources into our cloud environment.
  • Write Quality Code: Craft clean, efficient, and maintainable Python code following best practices and coding standards; experience with Java is considered a bonus.
  • Data Transformation & Modeling: Develop and optimize data transformation processes to deliver structured, actionable data to our consumers. Experience with data warehousing is a plus.
  • Cloud Integration: Utilize cloud services from Google Cloud Platform to build and optimize data solutions.
  • Problem Solving: Employ advanced debugging tools and techniques to identify, troubleshoot, and resolve complex issues within data pipelines.
  • Collaborative Development: Engage in code reviews, contribute to continuous integration/continuous deployment (CI/CD) practices, and work closely with peers in an agile development environment to enhance software quality.

 

Skills

  • Hands-On Data Engineering: 2.5 + years of experience building scalable data pipelines, with a strong focus on writing robust, maintainable Python code (Java is consider a plus).
  • Cloud Proficiency: Experience with one or more cloud platforms (Google Cloud, AWS, or Azure) and a solid understanding of their data services. Prior experience with Google Cloud Platform, including services like BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS, Cloud Composer (Airflow) is highly appreciated.
  • Data Transformation: Familiarity with data modeling and ETL processes; direct experience with data warehousing is advantageous but not essential.
  • Software Development Practices: Experience with version control tools (e.g. Git / Bitbucket), CI/CD pipelines (e.g., GitHub Actions, TeamCity, Jenkins), and unit testing frameworks (such as Pytest/Unittest for Python or Junit for Java).
  • Debugging Skills: Demonstrated ability to troubleshoot and resolve complex technical issues.
  • Bonus Skills: Familiar with any Infrastructure as Code tools (e.g. Terraform, Ansible, Chef), and hands-on experience with shell scripting.
  • Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

Well-being & Benefits

Emotionally and mentally balanced: We support you in dealing with life crises, maintaining stability through illness, and maintaining good mental health.

  • Empowering managers who value your ideas and decisions. Show your positive attitude, determination, and open-mindedness.
  • A professional, passionate, and fun workplace.
  • A modern office with fun and relaxing areas to boost creativity.
  • Continuous learning culture with coaching and support from team experts.
  • A culture where you can openly speak about mental health.

Physically thriving: We support you in managing your physical health by taking appropriate preventive measures and providing a workplace that helps you thrive. For example, Private healthcare and life insurance with premium benefits for you and discounts for your loved ones, healthier ways of working and check-ups.

Socially connected: We strongly believe in collaboration, inclusion and feeling connected to open up new perspectives and strengthen our self-confidence and well-being.

  • 24 days holiday, loyalty days, and bank holidays (including weekdays for weekend bank holidays).
  • Hybrid working model with 40% remote work.
  • Options for flexible working hours.
  • Enjoy retailer discounts, cultural and CSR activities, workshops, and more.

Financially secure: We support you in meeting personal financial goals during your active career and for the future.

  • Competitive income, performance-based promotions, and a sense of purpose.
  • Meal vouchers, bonuses for referrals

 

Interested in more: discover what our employees value in the Well-being & Benefits hub!

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
We welcome applications from all people and promote a positive, fair and inclusive work environment.

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Location & working pattern

Bucharest, Rumänien

- 24 days holiday, loyalty days, and bank holidays (including weekdays for weekend bank holidays). - Hybrid working model with 40% remote work. - Options for flexible working hours.
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