The enterprise workhorse that refuses to quit. For data engineering, Java is a powerhouse for building robust, scalable systems like custom ETL pipelines, distributed frameworks (hello, Hadoop), and real-time processing engines like Kafka Streams. Its JVM ecosystem and libraries (e.g., Apache Spark, Flink) make it a cornerstone for high-performance data applications where reliability matters. That said, Java’s verbosity can feel like writing a novel for every task, and its boilerplate-heavy style makes simple things unnecessarily painful. While its performance is solid and memory management reliable, it lacks the modern elegance of languages like Go or Python. Plus, debugging messy stack traces from poorly tuned JVMs is no picnic. Java thrives in large-scale, structured environments where maintainability and backward compatibility are king. It’s not the coolest language at the party, but when your data stack needs to scale like a Fortune 500 company, Java delivers—with plenty of paperwork.
Smile advertises a Data Analyst role embedded in a European open-source powerhouse of 1,800 people across nine countries. The core duties read like a complete data lifecycle: extract, clean, and...
read more »
Smile advertises a Data Analyst role embedded in a European open-source powerhouse of 1,800 people across nine countries. The core duties read like a complete data lifecycle: extract, clean, and prepare data; analyze for trends; build dashboards; define KPIs; and partner with business teams to deliver usable insights. Technically, you’re in an OSS-heavy stack: ETL/ELT and Big Data with Spark/Hadoop, cloud platforms (AWS, Azure, GCP), orchestration (Kubernetes, Docker), BI tools (Power BI, Tableau), SQL/NoSQL, programming in Python/Java/Scala/R, API work, CI/CD, and search engines Elasticsearch or Solr. The breadth is its selling point and its leash: a Data Analyst who also touches data engineering, backend work, and even search optimization risks role creep and dilution of depth. Still, you gain broad tooling exposure, practical enterprise challenges, and a clear path to cross-disciplinary credibility, not buzzword bingo.
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.
The BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of...
Stage Logiciel : Développement d'un outil d'extraction, d'analyse et de visualisation de données F/H
@ mbda
FR | 2025-12-26
MBDA’s student/alternance role reads like a grounded data tooling internship rather than a buzzword-filled data science job. You’ll build a graphical tool to search, extract, and analyze...
read more »
Stage Logiciel : Développement d'un outil d'extraction, d'analyse et de visualisation de données F/H
mbda
(FR) FULL TIME | JOB LISTED
MBDA’s student/alternance role reads like a grounded data tooling internship rather than a buzzword-filled data science job. You’ll build a graphical tool to search, extract, and analyze information from heterogeneous documents (DOORS, Word, PDF) and define a usable query model. Expect real, code-level work: Python for parsing and scripting, with Java or C# for the GUI, plus DOCX/XML handling and visualization libraries to show KPIs and dynamic graphs. The challenges sit at the intersection of data modeling, tooling, and user experience in a regulated defense context, with six-month horizons and fixed milestones. The upside: a credible pathway to a full-time role if you prove yourself, mentorship-rich environment, and exposure to mission-planning workflows. The downsides: defense sector constraints, potential patchwork data sources, and limited geographic flexibility.
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.
Smile advertises a Data Analyst role embedded in a European open-source powerhouse of 1,800 people across nine countries. The core duties read like a complete data lifecycle: extract, clean, and prepare data; analyze for trends; build dashboards; define KPIs; and partner with business teams to deliver usable insights. Technically, you’re in an OSS-heavy stack: ETL/ELT and Big Data with Spark/Hadoop, cloud platforms (AWS, Azure, GCP), orchestration (Kubernetes, Docker), BI tools (Power BI, Tableau), SQL/NoSQL, programming in Python/Java/Scala/R, API work, CI/CD, and search engines Elasticsearch or Solr. The breadth is its selling point and its leash: a Data Analyst who also touches data engineering, backend work, and even search optimization risks role creep and dilution of depth. Still, you gain broad tooling exposure, practical enterprise challenges, and a clear path to cross-disciplinary credibility, not buzzword bingo.
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.
Stage Logiciel : Développement d'un outil d'extraction, d'analyse et de visualisation de données F/H
mbda
(FR) FULL TIME | JOB LISTED
MBDA’s student/alternance role reads like a grounded data tooling internship rather than a buzzword-filled data science job. You’ll build a graphical tool to search, extract, and analyze information from heterogeneous documents (DOORS, Word, PDF) and define a usable query model. Expect real, code-level work: Python for parsing and scripting, with Java or C# for the GUI, plus DOCX/XML handling and visualization libraries to show KPIs and dynamic graphs. The challenges sit at the intersection of data modeling, tooling, and user experience in a regulated defense context, with six-month horizons and fixed milestones. The upside: a credible pathway to a full-time role if you prove yourself, mentorship-rich environment, and exposure to mission-planning workflows. The downsides: defense sector constraints, potential patchwork data sources, and limited geographic flexibility.
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.
