SAP Data Engineer II - FinTech

About Us:

At , data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make.

Through our products, partners and people, we make it easier for everyone to experience the world.

The Financial Systems team supports Finance by managing ’s financial data platform, including SAP, AWS, Snowflake, and connected systems. We are building simpler finance tools that provide better insights.

As a Data Engineer II, you will build and maintain data pipelines, models, and integrations. You will help ensure financial data is reliable, traceable, secure, and easy to use.

Your work will support regulated payments and e-money services, accurate reporting, operational visibility, and better decision-making as  grows globally. You may work on data extraction, warehouse modelling, data quality, monitoring, orchestration, performance, and governance.

The role will evolve as the organization grows, offering opportunities to develop your skills and take on new responsibilities.

• 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

• You have 3–5 years of relevant professional experience as a Data Engineer, BI Engineer, Analytics Engineer or in a similar data-focused role

• Hands-on experience with one of the following: : 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: SAP S/4
  
  HANA data structures and CDS/embedded extraction, BW/4
  
  HANA, and XSA and DB security concepts such as roles and privileges.

• Knowledge and experience of SAP-based financial reporting, or a track record of working closely with finance stakeholders, is a plus.

• 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.

• 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.

• 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.

• Experience with dbt and with descriptor file formats such as YAML;…