Senior Data Engineer
A Senior Data Engineer brings deep expertise in SQL development, data modeling, and stakeholder collaboration to deliver high-quality, reliable, and business-critical datasets. The role centers on building and optimizing SQL-driven data transformations, supporting analytical, operational, and regulatory reporting needs. Experience in banking or financial environments is a strong advantage. Python knowledge and BI tool experience (e.g., Tableau, Power BI) are valuable pluses that support automation, data preparation, and efficient analytics delivery. Responsibilities Develop and optimize complex SQL transformations supporting analytics, reporting, and financial/regulatory needs Work with and contribute to existing enterprise data models (Data Vault, dimensional, 3NF, domain driven structures) Ensure SQL logic is performant, maintainable, and aligned with modelling standards Implement and maintain data quality checks, validation rules, and SQL testing Maintain clear documentation, lineage, and metadata to support transparency and governance Support reduction of architectural debt and help maintain a clean, consistent data environment Build and maintain SQL centric ETL/ELT data pipelines Use Python where beneficial for automation, API integration, or workflow efficiency Implement ingestion patterns for batch, incremental, and near real time data flows Ensure monitoring, observability, and reliable operation of data workflows Partner with finance, risk, compliance, and business teams to translate requirements into high quality data solutions Work closely with data architects to ensure alignment with modelling standards Support troubleshooting across ingestion, modelling, and operational processes Contribute to platform evolution, engineering improvements, and roadmap initiatives Communicate effectively with both technical and business stakeholders Collaborate with platform and infrastructure teams to operate SQL workloads reliably in production Apply engineering best practices: version control, documentation, testing, code quality Requirements Bachelor’s or Master’s degree in a relevant field 5+ years in data engineering or SQL heavy backend roles Proven experience working with structured enterprise data models Experience in finance or banking is a strong advantage Expert level SQL (complex queries, tuning, optimization) Experience working with and extending established data models (Data Vault, dimensional, SCD, 3NF) Strong experience developing scalable SQL driven transformations Python is a strong plus for automation, API integrations, and workflow enhancement Experience with Tableau, Power BI, or other BI tools is a strong plus Experience working in banking, financial services, or regulated environments is a strong advantage Commitment to building reliable, maintainable, and well tested data solutions Strong focus on quality, monitoring, reliability, and automation Ownership mentality across the data lifecycle Ability to refine requirements and collaborate with technical and business teams Creative, proactive, and improvement oriented approach Strong communication and stakeholder engagement abilities Analytical, detail oriented, and proactive problem solver Comfortable in agile, iterative delivery environments English: fluent (written and spoken) German and/or French: nice-to-have Nice to have Experience with Temenos T24/Transact, Temenos Triple'A, or similar core banking platforms