Data Engineer

Emburse; Barcelona; Presencial; EUR 70.000 - 100.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible spending accounts

Generous paid time off

Health savings accounts

Insurance plans

Retirement savings plans

Looker/BI tools training

Team events

Descripción de la vacante

Emburse is seeking a Data Engineer to design and build data pipelines powering Emburse's SaaS analytics. You will populate data warehouses and lakes, ensure tenant data security, and support data science platforms, while integrating AI data solutions with Emburse products.

The role sits in the Platform Analytics team, a fast-moving, product-focused group delivering BI and data science capabilities. Expect collaboration across teams utilizing Snowflake, Databricks/Spark, AWS, and Looker.

Formación

• Bachelor's degree in Computer Science or related field or equivalent experience.
• Proficiency in Python with SDLC/production deployment experience.
• Experience working in a product-oriented environment with engineers and product managers.
• Experience with modern data pipelines or workflow management tools.
• Advanced SQL and experience with relational or columnar databases.

Responsabilidades

• Builds analytical tools to utilize, model and visualize data.
• Develops scripts to automate manual processes and monitor data pipelines.
• Understands OWASP and applies secure coding practices.
• Reads and reviews existing code; suggests improvements.
• Develops code in Python/Java/.NET for ETL data extraction, transformation and loading.
• Performs unit and integration testing when needed.

Conocimientos

Python

SQL

Java

Data modeling

Security awareness

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Snowflake

Databricks/Spark

Looker

Fivetran

Descripción del empleo

• 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 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 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