Senior Data & Analytics Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data & Analytics Engineer based in Spain. As a Senior Data & Analytics Engineer, you’ll take end-to-end ownership of a modern data platform and business intelligence layer within a fully remote, international environment. You’ll help transform complex data into scalable, trusted, and actionable insights for both customers and internal teams. The role combines data engineering, analytics engineering, and data product ownership, giving you broad influence across the data ecosystem. You’ll modernise existing BI capabilities while building robust pipelines, semantic models, customer-facing analytics, and governance practices. Your work will directly support better decisions and measurable environmental and operational impact in the aviation industry. This is a high-autonomy role for someone who enjoys solving complex problems, improving systems, and connecting technical solutions to real customer value. Accountabilities: Take end-to-end ownership of the data platform, including Databricks, Microsoft Fabric, scalable pipelines, and lakehouse architecture. Design, build, and operate robust ETL/ELT workflows supporting batch and near-real-time data processing. Establish and maintain data quality, reliability, observability, performance, and architectural standards across the platform. Define data contracts, architecture principles, and modular, scalable approaches while optimising platform costs and workload distribution. Own Power BI semantic models, KPIs, dimensional models, DAX performance, aggregations, and dataset refresh processes. Build and maintain customer-facing dashboards, embedded analytics, and data exports while ensuring consistent and trusted metrics. Enable governed self-service analytics and support secure, scalable multi-tenant data models. Translate customer and business needs into scalable data products, define reporting standards with Product, and identify opportunities to create additional value through data. Implement testing, validation, monitoring, alerting, CI/CD, versioning, and other engineering practices across data pipelines and BI assets. Lead the transition from an existing vendor-built BI solution by reverse-engineering pipelines, logic, and reports, reducing technical debt, and rebuilding toward a clean, product-grade architecture. Proactively identify patterns, anomalies, optimisation opportunities, and new insights that can generate measurable customer and business impact. Requirements: 5+ years of experience in data engineering or analytics engineering, ideally focused on customer-facing BI products. Proven experience building scalable data platforms and customer-facing analytics in SaaS or product-driven environments. Strong hands-on expertise with Databricks, including Spark/PySpark and Delta Lake. Strong experience with Microsoft Fabric and/or the broader Azure data ecosystem. Advanced Power BI expertise, including data modelling, DAX, performance optimisation, and semantic models. Advanced SQL skills and strong knowledge of dimensional modelling, particularly Kimball methodology. Strong understanding of lakehouse architecture, ETL/ELT design, multi-tenant data models, and embedded analytics. Experience implementing CI/CD for data pipelines and BI assets, as well as version control using tools such as Git. Strong engineering discipline, including writing reusable, modular, maintainable, and testable code. Experience with data quality, monitoring, validation, and testing practices. Knowledge of Azure infrastructure, including IAM and networking, is a plus. Familiarity with data quality frameworks such as Great Expectations is an advantage. Strong ownership and autonomy, with a focus on outcomes rather than simply completing assigned tasks. Product-oriented and impact-driven mindset, with the ability to connect technical data solutions to customer value. Proactive and pragmatic approach, with a preference for simple, effective solutions over unnecessary complexity. Strong communication skills and the ability to make complex technical concepts accessible to both technical and business stakeholders. Minimum English proficiency of C1. Willingness to participate in two annual one-week team events. Benefits: Fully remote working environment within Europe. Opportunity to take significant ownership of a modern data platform and BI ecosystem. Broad scope combining data engineering, analytics engineering, and data product ownership. Opportunity to work on technology designed to reduce food waste, fuel consumption, costs, and CO₂ emissions in the aviation industry. International and diverse working environment with colleagues across multiple countries. Strong emphasis on continuous learning, collaboration, creativity, and inclusion. Opportunity to build customer-facing analytics and data products with measurable real-world impact. Two annual one-week team events offering opportunities for in-person collaboration. High level of autonomy and flexibility in how you approach technical challenges and deliver outcomes. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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