8 Zeppelin Jobs

Revenir aux offres Stagiaire Business Analyst Data (LOB25-STA-06) Nature Data Business Analyst Contrat Stage 6 mois Exprience Moins d&apos1 an Lieu de travail Paris / Rgion parisienne A Propos Missions Le stage sinscrit dans le cadre de la mise en place dun SI denvergure pour la collecte et lutilisation des donnes Sociales Nominatives (DSN) pour un organisme du Secteur Public. Nes dune dcision politique pour la simplification des relations entre les entreprises et les organismes sociaux, la Dclaration Sociale Nominative est dsormais largement rependue et utilise par la majorit des entreprises et remplace la majorit des dclarations sociales franaises priodiques ou vnementielles. Les DSN embarquent une richesse mtier importante ainsi quune volumtrie trs consquente, avec des usages trs nombreux : interrogation de donnes en temps rel pour des actions telles que le contrle des entreprise, le calcul de donnes telles que les effectifs et la masse salariale ou lanalyse statistique. Face la richesse de ces donnes, cet organisme a lanc un important projet de refonte de sa brique SI de collecte et dutilisation des DSN dans une architecture BIG DATA. Sous la responsabilit dun Product Owner, vous serez intgr dans une quipe de Business Analyst de 7 personnes et vous interviendrez sur la dfinition et la validation des sprint et des livraisons des Data Engineer. Dans ce cadre, vous serez form et encadr sur les mthodologies de mise en uvre de solution DATA. Descriptif du poste Travaux Assurs Monte en comptence fonctionnelle sur les donnes de la DSN afin dapprhender les enjeux du projet, le primtre de donnes et les cas dusage affrents Apprentissage de la mthodologie agile (Scrum) Participation aux travaux de spcifications et de validation des sprints, avec un enjeu important sur lautomatisation des tests et les tests de non rgression. Dans cette optique, le stagiaire sera amen mettre en place des programmes dautomatisation qui ncessiteront quelques dveloppements. Le stage sadresse donc un profil dsireux dintervenir dans un cadre technico-fonctionnel. Participation aux crmonies agiles et aux travaux de pilotage Vous bnficierez de toute lexpertise de LOBELLIA Conseil sur le volet mtier et sur la conduite de projet agiles. Ce Stage Vous Permettra Dacqurir La vision architecturale dun systme BIG DATA denvergure Un cas pratique de comprhension et dutilisation de donnes denvergure Une vision de la dmarche dun projet DATA multi-quipe en mode agile Les technologies utilises sur les diffrents sujets sont : Suite Hadoop (Hdfs, Oozie, Yarn, Spark, Hive) Accs aux donnes : MobaXterm, Zeppelin, MIT Kerberos, DBeaver Langage de programmation : HQL (simili SQL) + Python Outils de travail : Sharepoint, Redmine, Git, Visual Studio Code, Excel Profil recherch Etudiant en dernire anne dcole dingnieur ou Master 2 scientifique. Qualits requises : Apptence technico-fonctionnelle Qualits rdactionnelles Esprit danalyse Rigueur Sens du service Aisance relationnelle Postuler Ce champs est requis. Ce champs est requis. Ce mail n&aposest pas valide. CV ** Ce champs est requis. Lettre de motivation Vous nous avez connus par... Les rseaux sociaux Un forum ou un vnement cole Une connaissance Autre Champs requis Fichier requis, au format pdf, poids infrieur 5Mo Merci, votre mail a t envoy. Show more Show less

Dear Candidate, We are looking for a Big Data Developer to build and maintain scalable data processing systems. The ideal candidate will have experience handling large datasets and working with distributed computing frameworks. Key Responsibilities: Design and develop data pipelines using Hadoop, Spark, or Flink. Optimize big data applications for performance and reliability. Integrate various structured and unstructured data sources. Work with data scientists and analysts to prepare datasets. Ensure data quality, security, and lineage across platforms. Required Skills & Qualifications: Experience with Hadoop ecosystem (HDFS, Hive, Pig) and Apache Spark. Proficiency in Java, Scala, or Python. Familiarity with data ingestion tools (Kafka, Sqoop, NiFi). Strong understanding of distributed computing principles. Knowledge of cloud-based big data services (e.g., EMR, Dataproc, HDInsight). Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

As a Data Science Manager in the Research and Development (R&D) team at our organization, you will play a crucial role in driving innovation through advanced machine learning and AI algorithms. Your primary responsibility will involve conducting applied research, development, and validation of cutting-edge algorithms to address complex real-world problems on a large scale. You will collaborate closely with the product team to gain insights into business challenges and product objectives, enabling you to devise creative algorithmic solutions. Your role will entail creating prototypes and demonstrations to validate new ideas and transform research findings into practical innovations by collaborating with AI Engineers and software engineers. In addition, you will be responsible for formulating and executing research plans, carrying out experiments, documenting and consolidating results, and potentially publishing your work. It will also be essential for you to safeguard intellectual property resulting from R&D endeavors by working with relevant teams and external partners. Furthermore, part of your role will involve mentoring junior staff to ensure adherence to established procedures and collaborating with various stakeholders, academic/research partners, and fellow researchers to deliver tangible outcomes. To excel in this position, you are required to possess a strong foundation in computer science principles and proficient skills in analyzing and designing AI/Machine learning algorithms. Practical experience in several key areas such as supervised and unsupervised machine learning, reinforcement learning, deep learning, knowledge-based systems, evolutionary computing, probabilistic graphical models, among others, is essential. You should also be adept in at least one programming language and have hands-on experience in implementing AI/machine learning algorithms using Python or R. Familiarity with tools, frameworks, and libraries like Jupyter/Zeppelin, scikit-learn, matplotlib, pandas, Tensorflow, Keras, Apache Spark, etc., will be advantageous. Ideally, you should have at least 2-5 years of applied research experience in solving real-world problems using AI/Machine Learning techniques. Additionally, having a publication in a reputable conference or journal related to AI/Machine Learning or holding patents in the field would be beneficial. Experience in contributing to open-source projects within the AI/Machine Learning domain will be considered a strong asset. If you are excited about this challenging opportunity, please refer to the Job Code DSM_TVM for the position based in Trivandrum. For further details, feel free to reach out to us at recruitment@flytxt.com.,

Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark , Python , and working with modern data engineering tools in cloud environments such as AWS . Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments Skills: ci/cd,zeppelin,pycharm,pyspark,etl tools,control-m,unit test cases,tableau,performance tuning,jenkins,qlikview,informatica,jupyter notebook,api integration,unix/linux,git,aws s3,hive,cloudera,jasper,airflow,cdc,pyspark, apache spark, python, aws s3, airflow/control-m, sql, unix/linux, hive, hadoop, data modeling, and performance tuning,agile methodologies,aws,s3,data modeling,data validation,ai/ml model development,batch integration,apache spark,python,etl pipelines,shell scripting,hortonworks,real-time integration,hadoop

Work Mode: Hybrid Interview Mode: Virtual (2 Rounds) Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark , Python , and working with modern data engineering tools in cloud environments such as AWS . Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments Skills: ci / cd , zeppelin , pycharm , pyspark , etl tools,control-m,unit test cases,tableau,performance tuning , jenkins , qlikview , informatica , jupyter notebook,api integration,unix/linux,git,aws s3 , hive , cloudera , jasper , airflow , cdc , pyspark , apache spark, python, aws s3, airflow/control-m, sql, unix/linux, hive, hadoop, data modeling, and performance tuning,agile methodologies,aws,s3,data modeling,data validation,ai/ml model development,batch integration,apache spark,python,etl pipelines,shell scripting,hortonworks,real-time integration,hadoop

Work Mode: Hybrid Interview Mode: Virtual (2 Rounds) Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark , Python , and working with modern data engineering tools in cloud environments such as AWS . Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments Skills: ci/cd,zeppelin,pycharm,pyspark,etl tools,control-m,unit test cases,tableau,performance tuning,jenkins,qlikview,informatica,jupyter notebook,api integration,unix/linux,git,aws s3,hive,cloudera,jasper,airflow,cdc,pyspark, apache spark, python, aws s3, airflow/control-m, sql, unix/linux, hive, hadoop, data modeling, and performance tuning,agile methodologies,aws,s3,data modeling,data validation,ai/ml model development,batch integration,apache spark,python,etl pipelines,shell scripting,hortonworks,real-time integration,hadoop

Role: PySpark DeveloperLocations:MultipleWork Mode: Hybrid Interview Mode: Virtual (2 Rounds) Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark, Python, and working with modern data engineering tools in cloud environments such as AWS. Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments

YOUR IMPACT Are you passionate about developing mission-critical, high quality software solutions, using cutting-edge technology,in a dynamic environment OUR IMPACT We are Compliance Engineering,a global team of more than 300 engineers and scientists whowork on the most complex, mission-critical problems. We: build and operate? a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm. have access to the latest technology andto massive amounts of structured and unstructured data. leverage modern frameworks to build responsive and intuitive UX/UI and Big Data applications. Compliance Engi??neering is looking to fillseveralbig data software engineering roles Your first deliverable and success criteria will be the deployment, in 2025, of newcomplex data pipelines and surveillance modelstodetect inappropriatetrading activity. ?HOW YOU WILL FULFILL YOUR POTENTIAL As a member of our team, you will: partner globally with sponsors,usersand engineering colleagues across multiple divisions to create end-to-end solutions, learn from experts, leverage varioustechnologies including; Java,Spark,Hadoop, Flink, MapReduce, HBase, JSON, Protobuf, Presto, Elastic Search, Kafka, Kubernetes be able to innovate and incubate new ideas, havean opportunity to work on a broad range of problems, includingnegotiatingdata contracts, capturing data quality metrics, processing large scaledata, buildingsurveillance detection models, be involved inthe full life cycle; defining,designing, implementing, testing, deploying, and maintaining software systems acrossour products. QUALIFICATIONS A successful candidate will possessthe followingattributes: A Bachelor's or Master's degreein Computer Science, Computer Engineering, or a similar field of study. Expertise in java, as well as proficiency with databasesand data manipulation. Experience in end-to-end solutions, automated testingand SDLC concepts. The ability (and tenacity) to clearly express ideas and arguments in meetings and on paper.? Experience inthe some offollowing is desired and can set you apart from other candidates: developing in large-scale systems, such as MapReduceon Hadoop/Hbase, data analysis using tools such as SQL, Spark SQL,Zeppelin/Jupyter, API design, such as to create interconnected services, knowledge of the financial industry and compliance or risk functions, abilityto influence stakeholders.