Senior Data Engineer – Python & BigQuery (f/m/x)
- Compensation
- Not disclosed
- Location
- Bucharest, 6A Dimitrie Pompeiu Blvd
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Full time
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Nice to have
- Experience with Infrastructure‑as‑Code (Terraform, Ansible, Chef).
- Knowledge of shell scripting.
- Experience in financial services or regulated environments
Full description
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 experienceas 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.