Data Engineer on Cloud (f/m/x)

Description

DB Global Technology is the technology centre of the company in Central and Eastern Europe, and the Bucharest team has been building global technology products and services since 2013.

You would join an international, agile team in the Private Bank's Data and Analytics domain, within the Global Data Platform subdomain. The team builds solutions for data warehousing, reporting and analytics so that operational and analytical users get the data they need.

The Global Data Platform is the Private Bank's new strategic data platform and runs on Google Cloud Platform. Working with Google as a close partner, the team is moving a large share of current on-premises applications to Google Cloud and building new ones there, in line with the bank's cloud strategy.

The team works with a hands-on engineering approach and invests in continuous learning, knowledge sharing and skill development.

Responsibilities

• Design, build and maintain fast, reliable batch and near real-time ETL pipelines that bring diverse data sources into the cloud environment.
• Write clean, efficient, maintainable Python that follows good practice and coding standards. Java experience is a bonus.
• Develop and tune data transformation processes that produce structured, usable data for consumers. Data warehousing experience is a plus.
• Use Google Cloud Platform services to build and improve data solutions.
• Debug and resolve complex issues in data pipelines using advanced tools and techniques.
• Take part in code reviews, support CI/CD practices and work with peers in an agile setting to raise software quality.

Requirements

• At least 2.5 years of experience building scalable data pipelines, with a strong focus on robust, maintainable Python. Java is a plus.
• Experience with at least one cloud platform (Google Cloud, AWS or Azure) and a solid grasp of its data services. Hands-on work with Google Cloud Platform is highly valued, including BigQuery, Dataflow (Apache Beam), CloudRun, CloudFunction, PubSub, GCS and Cloud Composer (Airflow).
• Understanding of data modelling and ETL processes. Direct data warehousing experience is helpful but not required.
• Experience with version control (such as Git or Bitbucket), CI/CD pipelines (such as GitHub Actions, TeamCity or Jenkins) and unit testing frameworks (such as Pytest or Unittest for Python, or JUnit for Java).
• Proven ability to troubleshoot and resolve complex technical problems.
• Bonus: familiarity with Infrastructure as Code tools (such as Terraform, Ansible or Chef) and hands-on shell scripting.
• Proven ability to use AI tools to raise productivity and improve workflows to solve business problems, while applying sound judgement to use data and AI outputs responsibly and ethically.

Conditions

Hybrid working model with 40% remote work.

Flexible working hours are available.

The company promotes a positive, fair and inclusive workplace and welcomes applications from all people.

Benefits

• 24 days of holiday, loyalty days and bank holidays (weekday replacements for bank holidays that fall on weekends).
• Private healthcare and life insurance with premium cover for you, and discounts for your family.
• Check-ups and healthier ways of working to support physical health.
• Mental health support, including help through life crises and a culture where you can talk openly about mental health.
• A modern office with relaxing areas, plus continuous learning with coaching from team experts.
• Competitive income, performance-based promotion, meal vouchers and referral bonuses.
• Retailer discounts, cultural and CSR activities, and workshops.
• Support with personal financial goals during your career and beyond.