Business Intelligence Engineer at GoCardless | Torre
Business Intelligence Engineer
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GoCardless

Business Intelligence Engineer

GoCardless
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Full-time

Legal agreement: To be defined

Compensation
EUR2.6k - 3.7k/month
~USD3.02k - 4.3k/month
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Hybrid (Riga, Latvia)
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Posted over 2 years ago

Requirements and responsibilities

- GoCardless is used for domestic and international payments by 75,000+ organisations and counting, processing more than $30 billion across 30 countries. - GoCardless is an award-winning London based fintech, with additional offices in Riga, Paris and Melbourne. We are looking for an experienced Business Intelligence Engineer to join our team at GoCardless. As a Business Intelligence Engineer, you will be responsible for defining and building GoCardless’s core data models, creating end-to-end BI solutions, and collaborating with various teams to enable data-driven decisions. You will work with a tech stack that includes Python, Looker, Google Cloud Platform, and BigQuery, and will be involved in developing coherent and performant data models, building BI tooling, and collaborating with data infrastructure engineers. If you are a self-starter with excellent SQL skills, experience with Big Data technologies, and a passion for data-driven decision-making, we encourage you to apply. The salary range for this position is €2600 - €3700 monthly (Gross). Responsibilities: - Develop coherent and performant data models for transforming large, complex, and disparate datasets into explorable, understandable, and accurate data products. - Build end-to-end BI solutions from ETL through to data modeling and on to front-end dashboards. - Collaborate with engineers to prototype, design, and build pipelines for analytic workloads. - Support people across the company to enable them to self-serve Business Intelligence through BI tools. - Build BI tooling that fully leverages the capabilities of Google Cloud Platform and BigQuery. - Collaborate with BI Analysts and other data teams to create a data architecture that powers deep-dive analysis and generates new business insights. - Collaborate with the team of Data Infrastructure Engineers to design and implement ingestion pipelines for new data sources.
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