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Deutsche Bank

Senior Data Engineer – Python & BigQuery (f/m/x)

Deutsche Bank is hiring a Senior Data Engineer – Python & BigQuery (f/m/x) in Bucharest, Romania. Level rates it ; you can apply on Deutsche Bank.

Level's read on this job

  • Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
  • Level classes it as a senior role.
  • Deutsche Bank has 1,100+ other open roles on Level.
  • Posted in the last few days.

AI in this role

Job Description:

Join DB Global Technology, Deutsche Bank’s technology center in Central and Eastern Europe. The Bucharest Technology Centre (BEX) delivers global tech products, driving the Bank's transformation. We foster a robust, hands-on engineering culture, dedicated to continuous learning, skill development, and networking. We develop applications for key business areas.

 

You will join the OneMIS stream, responsible for management, regulatory & risk reporting, and advanced analytics. Our mission includes enhancing data quality via KPIs and migrating data platforms to modern, cloud-native ecosystems. We operate in an agile environment, committed to responsible data practices.

 

Role Overview

We are looking for a Senior Data Engineer to design and deliver scalable data pipelines and high‑performance analytical solutions using SQL/BigQuery, Spark/PySpark, and Python on Google Cloud. This role focuses on building reliable, cloud‑native data products that enable advanced reporting, analytics, and decision‑making across the organization.


Responsabilities

  • Build scalable data pipelines: Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting.
  • Develop SQL and BigQuery solutions: Write and optimize advanced SQL transformations and build performant, cost‑efficient BigQuery data models.
  • Develop Python workflows: Implement scalable data processing solutions using Python and PySpark, ensuring maintainable and high‑quality code.
  • Design data models and ensure quality: Build robust data models and apply validation practices to maintain accuracy and reliability.
  • Build cloud‑native data solutions: Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms.
  • Optimize performance and reliability: Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance.
  • Collaborate using strong engineering practices: Work with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards.

 

Skills

  • 5+ years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems.
  • Strong expertise in SQL and hands‑on experience building performant datasets in BigQuery (or similar cloud data warehouses).
  • Proven experience with Python and PySpark for scalable data processing in distributed environments.
  • Solid understanding of data modeling, ELT/ETL patterns, and data quality best practices.
  • Experience with Google Cloud Platform, particularly BigQuery, Dataflow, Cloud Composer, GCS, or equivalent cloud data services.
  • Hands‑on experience building scalable data pipelines (batch and near real‑time) in a cloud‑native environment.
  • Proficiency with version control, CI/CD pipelines, and automated testing frameworks.
  • Ability to troubleshoot and optimize performance across compute, storage, and processing layers.
  • 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.

 

Nice to have

  • Experience with Infrastructure‑as‑Code (Terraform, Ansible, Chef).
  • Knowledge of shell scripting.
  • Experience in financial services or regulated environments

 

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 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-up's.

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 flexible working options
  • Enjoy retailer discounts, cultural and CSR activities, workshops, and more.

Financially secure: We support you to meet 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.

How we rate this

Senior Data Engineer – Python & BigQuery (f/m/x) at Deutsche Bank rates 24 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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