Data Engineer

Emburse
Madrid, Spain
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Clean Code Principles Java (Programming Language) .NET Framework Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Business Analytics Applications Data Analysis Unit Testing Software as a Service Databases Information Engineering
+21 more
Extract Transform Load (ETL) Data Security Data Systems Data Warehousing Relational Databases Software Debugging Python (Programming Language) Open Web Application Security Systems Development Life Cycle Standard Sql DataOps Software Deployment Web Analytics Snowflake Apache Spark Data Lakes Integration Tests Information Technology Looker Analytics Data Pipelines Databricks

Job description

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 BenefitsFlexible spending accounts Generous paid time off for every employee and flexible 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 ResponsibilitiesBuilds 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 RequirementsBachelor’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 PreferredExperience 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#J-*****-Ljbffr

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 #J-*****-Ljbffr

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