Data Engineer (Financial Systems, Fintech)

• As a Data Engineer II, you will be in charge of the development, performance, quality and scaling of the data pipelines and data models in your team’s domain, with a particular focus on data quality. You will work independently on well-scoped problems and will also contribute to technical decisions within the team
• Developing, testing and maintaining scalable data pipelines, data models and integrations that improve the quality, traceability and accessibility of financial data across our core systems
• Building and supporting the layers of our enterprise data warehouse - staging, core/integration and semantic/consumption - on SAP HANA, SAP Datasphere, AWS and Snowflake
• End-to-end ownership of data quality in the datasets and pipelines you deliver, including validation logic, monitoring, automated failure detection and root cause analysis
• Responsible for data loading, production monitoring and system performance, solving issues with data and data pipelines and prioritizing based on customer and finance process impact
• Engaging with finance and product stakeholders to understand their needs and translating requirements into logical and technical data designs, surfacing technical trade-offs early
• Applying the data governance, security and compliance controls required in a regulated payments and e-money environment, including roles and privileges, documentation and data contracts
• Writing high-quality, reusable and reviewed code that meets our coding standards, and delivering changes through Git and automated CI/CD pipelines
• Serving as a point of contact for technical and business stakeholders regarding data engineering issues, such as pipeline failures and data quality concerns, and supporting the training of key users
• Building AI consumption layer for rich semantic data models

Benefits

• Health insurance
• Free access to Headspace for you and your loved ones
• Global Employee Assistance Program
• Meditation and Breastfeeding rooms at the office
• Booking Cares - 2 days per year to volunteer and learn
• Life insurance
• Disability insurance
• Pension plan
• Annual paid time off
• Parental leave - 22 weeks
• Grandparent leave - 10 days
• Care leave - 10 days
• Bereavement leave - up to 4 weeks
• Anniversary leave
• Working from Home Furniture and Ergonomic Support
• Working from Abroad - up to 20 days per year
• Discounts & Wallet credits to spend on our products
• Upgrade to Booking.com Genius Level 3
• Friends & Family Booking.com discount vouchers
• Free access to online learning platforms
• Development and mentorship programs to support career growth
• Access to trainings and workshops
• Team development opportunities
• Local discount programs
• Game rooms in offices
• On-site meals, coffee and snacks including vegan options- Experience with dbt and with descriptor file formats such as YAML; exposure to orchestration tooling such as Apache Airflow is a plus
• You have 3–5 years of relevant professional experience as a Data Engineer, BI Engineer, Analytics Engineer or in a similar data-focused role, and hold a Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering or a related quantitative field
• You are independent, organized, flexible, proactive and result-oriented, with a proven ability to adopt new technologies and to own a process end to end
• Familiarity with Agile frameworks (Scrum or Kanban) and collaborative delivery tools such as Jira; familiarity with Data Product concepts, including data contracts and reusable, user-centric data models, is a plus
• Hands-on experience with one of the following is a plus: SAP HANA including XSA development, SAP Datasphere or SAP HANA Cloud, or Snowflake - combined with the ambition to grow across the full SAP and Snowflake stack
• Experience with SAP data products is a plus: SAP S/4HANA data structures and CDS/embedded extraction, BW/4HANA, and XSA and DB security concepts such as roles and privileges
• Experience leveraging AI-assisted tools to accelerate data modeling, query optimization and data analysis is a plus
• You have hands-on experience building and operating production-grade data pipelines and ETL/ELT solutions in cloud and hybrid environments, with a strong focus on scalability, reliability and data quality
• Superior attention to detail and quality, strong analytical and problem-solving skills, and the ability to manage multiple priorities in a quick turnaround environment
• You have practical experience with data modeling - dimensional modeling or Data Vault - and understand how to model, transform and expose data so it can be trusted and effectively used by analytics, finance and product stakeholders
• Excellent communication skills in English, both verbal and written, are essential; you are able to work effectively with finance stakeholders, product managers and engineers, and to translate requirements into robust technical solutions that enable high-quality data products
• Experience with Git concepts (GitHub/GitLab) is a must; experience with CI/CD and automated deployment pipelines is a plus
• Exposure to security concepts in Snowflake is a plus
• Experience building data exploration and visualization solutions and designing data storytelling for business users
• Strong knowledge of SQL, including stored procedures, functions and performance tuning on large enterprise datasets, is required; working knowledge of Python for data processing and automation is expected
• Knowledge and experience of SAP-based financial reporting, or a track record of working closely with finance stakeholders, is a plus