Back in the dark ages before everything lived in the cloud, sharing code was…an experience. Then came GitHub, promising to be the collaborative haven developers desperately needed. It took the core concept of version control—bless you, Linus Torvalds—and wrapped it in a social layer, effectively turning code into a public, searchable, and forkable playground. Quite clever, really, though one does wonder if all those public repositories are just a breeding ground for technical debt.
Today, GitHub is practically synonymous with open source, and Microsoft’s ownership feels… inevitable. It’s the default for many, eclipsing alternatives like GitLab and Bitbucket with sheer network effects. While it’s become a sprawling platform with project management tools and CI/CD pipelines, let’s be honest—most of us are still just using it to file issues and argue about whitespace. Still, it works, and in the world of software development, that’s often a victory in itself.
An analytics-heavy role that promises stakeholder-facing impact through SQL-driven data consolidation, PySpark work, and mission-critical dashboards. It asks you to translate business pain points...
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An analytics-heavy role that promises stakeholder-facing impact through SQL-driven data consolidation, PySpark work, and mission-critical dashboards. It asks you to translate business pain points into analytics problems, become the banking domain SME, and stitch data from multiple sources into decision-ready views. Expect ad-hoc analyses, pre/post campaign evaluation, and in-campaign tracking, with a heavy emphasis on dashboard design over robust data pipelines. The requirements skew early-career: a bachelor's degree and up to four years' experience, with a preference for practical BI/marketing analytics exposure. The lack of explicit cloud, data governance, or production-data responsibilities is notable; this is less about scalable data platforms and more about quick insights and presentation. In a FinTech/FinBank context, the role stands out for domain exposure but risks immaturity in tooling breadth.
This role positions itself as the bridge between stakeholders and data, promising to translate needs into analytics problems, consolidate data from multiple sources into integrated views, and...
read more »
This role positions itself as the bridge between stakeholders and data, promising to translate needs into analytics problems, consolidate data from multiple sources into integrated views, and deliver decision-ready dashboards with SQL and PySpark while supporting pre-, in-, and post-campaign tracking. It leans junior-friendly—open to fresh graduates up to four years’ experience—and values strong project management and communication. What stands out is the lean, hands-on stack: SQL, PySpark, and dashboards in a banking/FinTech context, with a preference for practical analytics over glitzy ML. The gaps are notable: no explicit data platform or governance details, no tooling beyond SQL/PySpark, and little clarity on production responsibilities or career progression. Banking work implies regulatory rigor and security demands; without specifics on architecture and reliability, expect a roll-your-sleeves-and-hope-for-the-best day-to-day.
The Fundamentals of Analytics Engineering gives a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering. It's a book that teaches concepts and best practices, not just tools and technologies.
A remote, 3-month role supporting data and analytics for multiple organizational partners, primarily focusing on inventory and sell-through analysis. The position involves designing analyses and...
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A remote, 3-month role supporting data and analytics for multiple organizational partners, primarily focusing on inventory and sell-through analysis. The position involves designing analyses and reports, collaborating with Data Scientists, and guiding partner investments. Its differentiator lies in cross-org visibility; the risk includes relying heavily on self-service data solutions that may not always be reliable or timely.
Intern - Quality Assurance Automation Engineer - F/M
@ sap
FR | 2025-12-26
SAP’s 6-month Paris internship asks a QA Automation Engineer to dive into SAP Analytics Cloud, collaborate in Scrum squads, and shape end-to-end test strategies for UI and API layers using Jasmine...
read more »
Intern - Quality Assurance Automation Engineer - F/M
sap
(FR) INTERNSHIP | JOB LISTED
SAP’s 6-month Paris internship asks a QA Automation Engineer to dive into SAP Analytics Cloud, collaborate in Scrum squads, and shape end-to-end test strategies for UI and API layers using Jasmine and Selenium. It’s heavy on toolchain: Gherkin, Cucumber/Robot, Java, JavaScript/TypeScript (UI5/React), Git, Jenkins, Docker, Kubernetes, plus an ambitious nod to an LLM-based test generator. The mix of front-end components and cloud analytics aligns with real-world demand, but the permanent perks are undefined in a six-month stint and the bilingual English/French requirement tightens the gate. The role promises constant learning and a window into large-scale enterprise CI/CD, with opportunities to influence QA approaches across global SAP teams. The risks? Bureaucracy, a vendor-light internship label, and a credential boost with a cloud behemoth that isn’t exactly a startup. Overall, practical, not flashy, valuable if you want visibility into enterprise analytics tooling.
This position demands Japanese language proficiency and involves data analysis within Merpay's credit-related services, with an emphasis on leveraging latest AI trends like LLMs. The unique...
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This position demands Japanese language proficiency and involves data analysis within Merpay's credit-related services, with an emphasis on leveraging latest AI trends like LLMs. The unique challenge lies in managing rapid PDCA cycles while transforming analysis processes through cutting-edge AI techniques, which carries the risk of technological obsolescence. The role offers the chance to influence product decisions directly, but bears the inherent danger of being caught in the fast-paced, high-stakes environment of fintech analytics.
Six-month internship at SAP Paris as QA and Automation Engineer. You join Scrum teams to master SAP Analytics Cloud, align with delivery workflows, analyze functional needs, and design/execute...
read more »
Intern - Ingénieur.e Assurance Qualité & Automatisation - F/H
sap
(FR) INTERNSHIP | JOB LISTED
Six-month internship at SAP Paris as QA and Automation Engineer. You join Scrum teams to master SAP Analytics Cloud, align with delivery workflows, analyze functional needs, and design/execute automated UI and API tests with Jasmine and Selenium. You will track defects, validate fixes, and help stitch CI/CD pipelines; expect to contribute to test generation and LLM-based error analysis. The tech stack reads like a checklist: Java, JavaScript/TypeScript (UI5 and React), Selenium, Jasmine, Cucumber or Robot, Git/GitHub, Jenkins, Docker, Kubernetes, plus Gherkin knowledge a plus and basic AI/ML concepts. It sits inside SAP’s cloud analytics ecosystem (SAP Analytics Cloud, SAP BTP) with teams across Paris and the world. The role promises learning and well-being, but as an internship it tests you more than it rewards, and the breadth of tooling can be overwhelming for a six-month window.
Masthead is a data reliability platform built for Google Cloud, focused on detecting anomalies and ensuring smooth data pipeline operations. It offers real-time notifications for data issues and pipeline errors without direct access to your sensitive data.
This 6-month renewable bioinformatics Business Analyst role supports digital transformation in advanced research, focusing on biological data analysis and developing innovative solutions. A key...
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This 6-month renewable bioinformatics Business Analyst role supports digital transformation in advanced research, focusing on biological data analysis and developing innovative solutions. A key differentiator is expertise in graph technologies like Neo4j and algorithms such as GNN; a risk involves the reliance on specialized skills that may not be fully covered by current team expertise.
An analytics-heavy role that promises stakeholder-facing impact through SQL-driven data consolidation, PySpark work, and mission-critical dashboards. It asks you to translate business pain points into analytics problems, become the banking domain SME, and stitch data from multiple sources into decision-ready views. Expect ad-hoc analyses, pre/post campaign evaluation, and in-campaign tracking, with a heavy emphasis on dashboard design over robust data pipelines. The requirements skew early-career: a bachelor's degree and up to four years' experience, with a preference for practical BI/marketing analytics exposure. The lack of explicit cloud, data governance, or production-data responsibilities is notable; this is less about scalable data platforms and more about quick insights and presentation. In a FinTech/FinBank context, the role stands out for domain exposure but risks immaturity in tooling breadth.
This role positions itself as the bridge between stakeholders and data, promising to translate needs into analytics problems, consolidate data from multiple sources into integrated views, and deliver decision-ready dashboards with SQL and PySpark while supporting pre-, in-, and post-campaign tracking. It leans junior-friendly—open to fresh graduates up to four years’ experience—and values strong project management and communication. What stands out is the lean, hands-on stack: SQL, PySpark, and dashboards in a banking/FinTech context, with a preference for practical analytics over glitzy ML. The gaps are notable: no explicit data platform or governance details, no tooling beyond SQL/PySpark, and little clarity on production responsibilities or career progression. Banking work implies regulatory rigor and security demands; without specifics on architecture and reliability, expect a roll-your-sleeves-and-hope-for-the-best day-to-day.
A remote, 3-month role supporting data and analytics for multiple organizational partners, primarily focusing on inventory and sell-through analysis. The position involves designing analyses and reports, collaborating with Data Scientists, and guiding partner investments. Its differentiator lies in cross-org visibility; the risk includes relying heavily on self-service data solutions that may not always be reliable or timely.
Intern - Quality Assurance Automation Engineer - F/M
sap
(FR) INTERNSHIP | JOB LISTED
SAP’s 6-month Paris internship asks a QA Automation Engineer to dive into SAP Analytics Cloud, collaborate in Scrum squads, and shape end-to-end test strategies for UI and API layers using Jasmine and Selenium. It’s heavy on toolchain: Gherkin, Cucumber/Robot, Java, JavaScript/TypeScript (UI5/React), Git, Jenkins, Docker, Kubernetes, plus an ambitious nod to an LLM-based test generator. The mix of front-end components and cloud analytics aligns with real-world demand, but the permanent perks are undefined in a six-month stint and the bilingual English/French requirement tightens the gate. The role promises constant learning and a window into large-scale enterprise CI/CD, with opportunities to influence QA approaches across global SAP teams. The risks? Bureaucracy, a vendor-light internship label, and a credential boost with a cloud behemoth that isn’t exactly a startup. Overall, practical, not flashy, valuable if you want visibility into enterprise analytics tooling.
This position demands Japanese language proficiency and involves data analysis within Merpay's credit-related services, with an emphasis on leveraging latest AI trends like LLMs. The unique challenge lies in managing rapid PDCA cycles while transforming analysis processes through cutting-edge AI techniques, which carries the risk of technological obsolescence. The role offers the chance to influence product decisions directly, but bears the inherent danger of being caught in the fast-paced, high-stakes environment of fintech analytics.
Intern - Ingénieur.e Assurance Qualité & Automatisation - F/H
sap
(FR) INTERNSHIP | JOB LISTED
Six-month internship at SAP Paris as QA and Automation Engineer. You join Scrum teams to master SAP Analytics Cloud, align with delivery workflows, analyze functional needs, and design/execute automated UI and API tests with Jasmine and Selenium. You will track defects, validate fixes, and help stitch CI/CD pipelines; expect to contribute to test generation and LLM-based error analysis. The tech stack reads like a checklist: Java, JavaScript/TypeScript (UI5 and React), Selenium, Jasmine, Cucumber or Robot, Git/GitHub, Jenkins, Docker, Kubernetes, plus Gherkin knowledge a plus and basic AI/ML concepts. It sits inside SAP’s cloud analytics ecosystem (SAP Analytics Cloud, SAP BTP) with teams across Paris and the world. The role promises learning and well-being, but as an internship it tests you more than it rewards, and the breadth of tooling can be overwhelming for a six-month window.
This 6-month renewable bioinformatics Business Analyst role supports digital transformation in advanced research, focusing on biological data analysis and developing innovative solutions. A key differentiator is expertise in graph technologies like Neo4j and algorithms such as GNN; a risk involves the reliance on specialized skills that may not be fully covered by current team expertise.
