Emburse data engineers develop the data pipelines and systems in the central platform empowering Emburse's SaaS productsAs a data engineer, you will build the pipelines that populate the data warehouse and data lakes, implement tenant data security, support the data science platforms and techniques, and integrate AI data solutions and APIs with Emburse products and analyticsThe role is based within the Emburse Platform analytics team, a fast moving and product-focused team responsible for delivering next generation business intelligence and data science capabilities across the businessEmburse, known for its innovation and award-winning technologies employ modern technologies including Snowflake, Data Bricks/Spark, AWS and LookerIn this role you will have access to the best and brightest minds in our industry to grow your experience and career within EmburseSDLC processes are followed, including adopting agile-based processes/meetings, peer code-reviews, and technical preparations required for scheduled releasesUnderstands product roadmap and how one contributes to the overall objectivesCapable at prioritizing tasksEstimates their own workLearns and applies secure software development practices, reviews code for vulnerabilities and raises awareness of secure programming practicesOptimizes processes, fixes bugs of moderate complexity and demonstrates proficient debugging skillsReviews code for team members,



providing in-depth commentsDevelops new features or enhancements with minimal supervisionDelivers medium level refactoringImplements unit testing and integration testing where neededProduces quality technical documentationMakes technical documentation/knowledge base contributions and technical team presentationsGives constructive feedback to team membersUnderstanding of industry jargon and business conceptsRaises roadblocks and updates estimations as neededBenefitsFlexible spending accountsGenerous paid time off for every employee and versátil work schedulesPaid leave for new parentsVolunteering opportunitiesHealth savings accounts (HSA)Medical, dental, vision, disability and life insurance plansGenerous match to pre- or post-tax retirement savings accountsFinancial planning servicesProgram in partnership with eCornell to grow their knowledge and their careersDelicious supply of snacks and beveragesQuarterly outings and Friday get-togethers to build a strong community at workKey ResponsibilitiesBuilds analytical tools to utilize, model and visualize data4+ years of data engineering experience related to data acquisition, data pipeline or analytics systemsDevelops scripts to automate manual processes, address data quality, enable integration or monitor processesUnderstanding of OWASPAbility to read and understand existing code and offer recommendations for improvementDevelops code (e.g. python,



Java or .net, or with specialized ETL tools) for the extraction, transformation, and loading of data from a variety of data sourcesUnderstands testing and integration testing techniquesSelf-sufficient in at least one large area of the data acquisition, data pipeline, analytics codebase, semantic views and an understanding of how a handful of key sub-systems interoperateUnderstands relational databases, columnar databases, development frameworks, and commonly used industry librariesCan interpret ad-hoc requests for data and translate these into the applicable data operationsRequirementsBachelor's degree in Computer Science or related field, or equivalent years’ experienceExperience with Python in a full SDLC/production deployment environmentExperience working in a product-oriented environment alongside software engineers and product managersExperience working with a modern data pipeline or data workflow management toolAdvanced working SQL knowledge and moderate experience working with relational or columnar databasesPreferredExperience with AWS servicesExperience working with SnowflakeExperience working with Looker or an equivalent Business Intelligence suiteExperience working with Fivetran or an equivalent ETL/ELT suiteExperience with Databricks or an equivalent Spark-based suiteFinancial Industry experience preferredExperience working with semantic data modeling for AI optimizationExperience working with a modern scalable data lake or data warehouses
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📌 Data Engineer (Barcelona)
🏢 Emburse
📍 Barcelona