Senior Data Platform Engineer

hace 2 días

Madrid, España Ares Consultores A tiempo completo

.Ebury is a hyper-growth FinTech firm, named as one of the top 15 European Fintechs to work for by AltFi.
We offer a range of products including FX risk management, trade finance, currency accounts, international payments, and API integration.
Position: Senior Data Platform Engineer Location: Madrid Office - Hybrid: 4 days in the office, 1 day working from home Join Our Data Team at Ebury Ebury's strategic growth plan would not be possible without our Data team, and we are seeking a Senior Data Engineer to join our Data Platform Engineering team
Our data mission is to develop and maintain Ebury's Data Warehouse and serve it to the whole company, where Data Scientists, Data Engineers, Analytics Engineers, and Data Analysts work collaboratively to: Build ETLs and data pipelines to serve data in our platform.
Provide clean, transformed data ready for analysis and used by our BI tool.
Develop department and project-specific data models and serve these to teams across the company to drive decision making.
Automate end solutions so we can all spend time on high-value analysis rather than running data extracts.
We are looking for a skilled Senior Data Engineer with a strong focus on building and optimizing data platforms to join our growing team.
In this role, you will be responsible for developing, enhancing, and maintaining robust frameworks and best practices to support our analytics and ML initiatives.
You will work closely with data analysts and other engineering teams to ensure our data platform is scalable, secure, and efficient.
About Our Technology and Data Stack We utilize the following tools: Google Cloud Platform as our main Cloud provider Apache Airflow as orchestration tool Docker as PaaS to deliver software in containers dbt for data transformation Looker and Looker Studio as BI tools Github as code management tool Jira as project management tool Synq as a data observability tool Among other third-party tools such as Hevodata, MonteCarlo, Synq… Responsibilities Establish performance monitoring to track the speed and efficiency of data processing and analysis, and address bottlenecks or slowdowns as needed.
Participate in data modelling reviews and discussions to validate the model's accuracy, completeness, and alignment with business objectives.
Work on reducing technical debt by addressing code that is outdated, inefficient, or no longer aligned with best practices or business needs.
Help to implement data governance policies, including data quality standards, data access control, and data classification.
Collaborate with data scientists, analysts, and stakeholders to understand data requirements and translate them into platform capabilities.
Automate data ingestion, transformation, testing, and integration processes to enhance data accessibility and data quality.
Evaluate and integrate new data tools and technologies to continuously improve the platform's capabilities

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