At Emburse, you’ll not just imagine the future – you’ll build it. As a leader in expense intelligence, we are creating a future where technology drives business value and inspires extraordinary results. Software Engineering Architects, deploys, and maintains production-grade Python microservices, serverless components (AWS Lambda), batch workers, web services, and shared core libraries across the analytics ecosystem Constructs backend infrastructure powering AI analytics solutions, incorporating LLM and natural language query translation engines like Snowflake Cortex, controlling dialog state, guaranteeing multi-tenant data isolation before execution, and optimizing throughput and resource utilization Authors clean, resilient codebase backed by comprehensive test suites while directing GitHub Actions continuous integration and continuous deployment pipelines for automated compilation, verification, security inspection, and production releases Safeguards system configuration and secrets using key-pair authentication, parameter management, and service credentials while proactively updating software dependencies based on vulnerability scanning metrics Data Engineering Constructs and manages ingestion and transformation workflows utilizing Airflow, AWS Glue, Spark, and Snowflake dynamic tables to feed multi-tier lakehouse environments from diverse sources Engineers automated data cleansing and enrichment routines integrating machine learning models and record reconciliation methods, while safely executing massive historical data re-processing Architects robust multi-tenant security frameworks in Snowflake employing row-level policies, secure functions,



and isolated access controls across integral cloud infrastructure regions Executes data governance protocols and privacy compliance workflows, including systematic tenant data purging across all analytical storage tiers Develops internal platform analytics modules to track, aggregate, and report infrastructure consumption and operational expenditures across cloud vendor ecosystems Follows SDLC processes, including adopting agile-based processes, peer code-reviews, and technical preparations required for scheduled releases and demos. Partners with product, analytics and data science team to drive requirements that take into account all parties' needs Establishes monitoring, responds to alerts and resolves issues within data pipelines Streamlines operational processes, resolves critical system defects, performs advanced codebase refactoring, and exhibits expert troubleshooting capabilities across application code, cloud infrastructure, and analytical queries Authors comprehensive technical documentation, operational runbooks, and detailed data dictionaries to support platform capabilities Spearheads onboarding initiatives and provides technical coaching and mentorship to junior staff members Demonstrated background of at least six years architecting enterprise software solutions and big data platforms in operational environments. Bachelor’s degree in Computer Science or related field,



or equivalent years’ experience Advanced proficiency in Python engineering, spanning distributed microservices, internal modules, RESTful interface design, unit testing frameworks, and GitHub Actions release pipelines rather than ad-hoc scripting. Expert SQL query optimization, data modeling techniques, and extensive background delivering cloud warehouse architectures using Snowflake. Proven mastery deploying and orchestrating data processing flows in live production through Apache Airflow. Hands-on expertise utilizing Amazon Web Services ecosystems, including AWS Lambda, S3 storage, Glue jobs, IAM policies, Key Management/Secrets Manager, and EventBridge integration. Deep comprehension of multi-tenant security architecture—incorporating row-level access policies, fine-grained access governance, strict tenant isolation, and compliant handling of restricted financial assets across international cloud regions. Snowflake advanced features: row access policies, secure views, dynamic tables, stored procedures, Cortex AI / Cortex Analyst, semantic views. Experience building LLM-powered or text-to-SQL features, or other GenAI applications in production. Spark (AWS Glue or Databricks). Looker or an equivalent BI platform, including embedded analytics. Infrastructure as code and GitHub Actions. Experience with ML-assisted data matching or entity resolution. Financial, expense or travel industry experience. A Culture That Empowers – Competitive pay, flexible work, and an inclusive, collaborative environment that In addition to federal law requirements, Emburse complies with applicable state and local laws governing nondiscrimination in employment in every location where the company has facilities.

📌 Senior Data Engineer (España)
🏢 Emburse
📍 España