Emburse data engineers develop the data pipelines and systems in the central platform empowering Emburse's SaaS products

As 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 analytics

The 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 business
Emburse, known for its innovation and award-winning technologies employ modern technologies including Snowflake, Data Bricks/Spark, AWS and Looker
In this role you will have access to the best and brightest minds in our industry to grow your experience and career within Emburse
SDLC processes are followed, including adopting agile-based processes/meetings, peer code-reviews, and technical preparations required for scheduled releases
Understands product roadmap and how one contributes to the overall objectives
Capable at prioritizing tasks
Estimates their own work
Learns and applies secure software development practices, reviews code for vulnerabilities and raises awareness of secure programming practices
Optimizes processes, fixes bugs of moderate complexity and demonstrates proficient debugging skills
Reviews code for team members, providing in-depth comments
Develops new features or enhancements with minimal supervision
Delivers medium level refactoring
Implements unit testing and integration testing where needed




Produces quality technical documentation
Makes technical documentation/knowledge base contributions and technical team presentations
Gives constructive feedback to team members
Understanding of industry jargon and business concepts
Raises roadblocks and updates estimations as needed
Benefits Flexible spending accounts
Generous paid time off for every employee and adaptable work schedules
Paid leave for new parents
Volunteering opportunities
Health savings accounts (HSA)
Medical, dental, vision, disability and life insurance plans
Generous match to pre- or post-tax retirement savings accounts
Financial planning services
Program in partnership with eCornell to grow their knowledge and their careers
Delicious supply of snacks and beverages
Quarterly outings and Friday get-togethers to build a strong community at work
Key Responsibilities Builds analytical tools to utilize, model and visualize data
4+ years of data engineering experience related to data acquisition, data pipeline or analytics systems
Develops scripts to automate manual processes, address data quality, enable integration or monitor processes
Understanding of OWASP
Ability to read and understand existing code and offer recommendations for improvement
Develops 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 sources
Understands testing and integration testing techniques
Self-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 interoperate
Understands relational databases, columnar databases, development frameworks, and commonly used industry libraries
Can interpret ad-hoc requests for data and translate these into the applicable data operations
Requirements Bachelor's degree in Computer Science or related field, or equivalent years’ experience
Experience with Python in a full SDLC/production deployment environment
Experience working in a product-oriented environment alongside software engineers and product managers
Experience working with a modern data pipeline or data workflow management tool
Advanced working SQL knowledge and moderate experience working with relational or columnar databases
Preferred Experience with AWS services
Experience working with Snowflake
Experience working with Looker or an equivalent Business Intelligence suite
Experience working with Fivetran or an equivalent ETL/ELT suite
Experience with Databricks or an equivalent Spark-based suite
Financial Industry experience preferred
Experience working with semantic data modeling for AI optimization

Experience working with a modern scalable data lake or data warehouses

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📌 Data Engineer (Barcelona)
🏢 Emburse
📍 Barcelona