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

Description

The company's technology centre in Bucharest builds global technology products that support the bank's transformation. The team works in a hands-on engineering culture that values continuous learning, skill growth and networking, and it builds applications for the bank's key business areas.

You will join the OneMIS stream, which covers management, regulatory and risk reporting, and advanced analytics. Work includes raising data quality through KPIs and moving data platforms to modern cloud-native systems. The team works in an agile way and takes responsible data practices seriously.

As a Senior Data Engineer, you will design and deliver scalable data pipelines and fast analytical solutions on Google Cloud, using SQL, BigQuery, Spark, PySpark and Python. The goal is reliable cloud-native data products that power reporting, analytics and decisions across the organisation.

Responsibilities

• Design and deliver batch and real-time ETL and ELT pipelines across cloud environments for analytics and reporting.
• Write and tune advanced SQL transformations and build efficient, cost-aware BigQuery data models.
• Build scalable data processing in Python and PySpark, keeping the code maintainable and of high quality.
• Build sound data models and apply validation so that data stays accurate and reliable.
• Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub and GCS to build and run modern data platforms.
• Find and fix complex pipeline problems, and keep improving compute, storage and processing performance.
• Work with engineering, analytics and business teams, and contribute to CI/CD, code reviews and testing standards.

Requirements

• At least 5 years as a Data Engineer, building scalable pipelines and working with cloud-based data ecosystems.
• Strong SQL skills and hands-on experience building high-performance datasets in BigQuery or a similar cloud data warehouse.
• Proven experience with Python and PySpark for scalable data processing in distributed environments.
• Solid grasp of data modelling, ELT and ETL patterns, and data quality best practices.
• Experience with Google Cloud Platform, especially BigQuery, Dataflow, Cloud Composer and GCS, or equivalent cloud data services.
• Hands-on experience building batch and near real-time pipelines in a cloud-native setting.
• Proficiency with version control, CI/CD pipelines and automated testing frameworks.
• Ability to troubleshoot and optimise performance across compute, storage and processing layers.
• Proven ability to use AI tools to raise productivity and improve workflows for business problems, with sound judgment on responsible and ethical use of data and AI outputs.
• Experience with Infrastructure as Code tools such as Terraform, Ansible or Chef.
• Knowledge of shell scripting.
• Experience in financial services or regulated environments.

Conditions

Hybrid working model with flexible working options.

24 days of holiday, loyalty days, and bank holidays, including weekdays that fall in place of weekend bank holidays.

We welcome applications from all people and aim for a fair, inclusive workplace.

Benefits

• Competitive income, performance-based promotions and a clear sense of purpose.
• Financial support for personal goals during your career and beyond, plus meal vouchers and bonuses for referrals.
• Private healthcare and life insurance with premium cover for you, and discounts for your loved ones.
• Preventive health measures, check-ups and healthier ways of working.
• Support through personal crises, illness and mental health, in a culture where you can talk openly about mental health.
• Continuous learning with coaching and support from team experts.
• A modern office with relaxed areas to spark creativity.
• Social activities, collaboration and inclusion events, retailer discounts, cultural and CSR activities, and workshops.
• Empowering managers who value your ideas and decisions.