Data Engineer

🕒 vor 3 Tagen

🇫🇷 Frankreich – Remote

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

🚰 Dateningenieur

👻 Geisterscore 15%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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lemlist

WebsiteLinkedInAlle Stellen

51 - 200 Mitarbeiter

Gegründet 2018

💼 Beratung

📣 Marketing

📦 Logistik

Consulting • Marketing • Logistics

lemlist ist eine SaaS-Plattform für Verkaufsengagement und -akquise, die Vertriebsteams dabei unterstützt, qualifizierte Leads zu finden, anzureichern und zu erreichen. Sie bietet eine große Lead-Datenbank, E-Mail- und Telefonverifizierung, KI-gestützte Personalisierung und automatisierte Multichannel-Outreach über E-Mail, LinkedIn, WhatsApp und Anrufe sowie Zustellwerkzeuge (lemwarm) und Integrationen/API, um in bestehende CRMs und Stacks zu passen.

Beschreibung

• Design, build, and improve a scalable data platform supporting product data solutions • Collaborate with product and business teams to build scalable and agile solutions • Define technical standards and contribute to data platform architecture and deployment decisions based on the strategic product roadmap • Develop, deploy, and manage efficient data platforms and automated data pipelines using cloud-based and on-premise technologies • Design, maintain, and enhance key data product features for quality, certification, accessibility, and integration • Analyze and develop data operations and pipelines following enterprise guidelines and best practices • Apply data quality processes, governance, and catalog/glossary curation • Maintain and improve existing pipelines by integrating new features and change requests using an agile approach • Ensure data quality, lineage, versioning, and observability across the stack • Support CI/CD and release processes • Onboard the existing data platform end to end, including sources, ingestion jobs, warehouse models, orchestration, BI layer, and consumers • Audit the current stack, identify risks and gaps, and estimate their costs • Deliver a quick win such as fixing an unreliable pipeline, resolving a cost anomaly, or making a critical dataset trustworthy • Create and validate a technical roadmap covering target architecture, technology choices, and migration path • Improve data engineering standards for repository structure, Git workflow, CI/CD, environments, code review, and deployment • Scale the data platform with data volume and product growth while controlling pipeline costs • Reduce incidents and time-to-detect for critical datasets • Implement observability with freshness, volume, and schema checks, alerting, SLAs, and ownership • Enable new product analytics, in-product data, and ML/AI use cases • Serve as a data architecture reference for the C-suite and Product

🎯 Anforderungen

• Master's degree in computer science, distributed systems, data engineering, engineering or equivalent • 5+ years experience in intensive data platforms in the context of Big Data and cloud infrastructures/platforms • Strong background in Big Data architecture approaches and DBMS/Data Warehouse modelling, optimisation, and management • Deep knowledge of SQL, Python and Spark-related programming languages • Experience with data warehouses and lakes, including BigQuery, Snowflake, Databricks, Storage, and Delta Lake • Extensive expertise in data preparation, integration, modelling, and governance processes • Proven experience designing and managing end-to-end production-ready solutions • Experience developing, optimising, and maintaining scalable data ingestion and transformation pipelines using modern data technologies, including Pub/Sub and Kafka • Familiarity with DataOps: Git, Docker, CI/CD practices including Jenkins, and deployment workflows in a data engineering environment • Experience ensuring data quality, consistency, and performance across data platforms while applying data governance principles • Strong analytical mindset and ability to solve complex data challenges and continuously improve data solutions • Ability to thrive in a demanding, fast-growing environment with high ownership, structure, and execution speed • Fluent in French and English • Nice to have: hands-on experience with NoSQL, Search DBMS, or OLAP DBMS • Nice to have: first experience in B2B SaaS

🏖️ Vorteile

• Competitive salary and company bonus (up to 18K€ per year depending on company’s performance) • 38 days of holidays/year • Alan Blue: Comprehensive 100% premium medical coverage for you and your family • Swile Meal Tickets: Enjoy daily meal tickets to fuel productivity • Navigo Card: Seamless commuting with a 100% covered Navigo card • Laptop, tools, and equipment needed for the job • Team building: annual company gathering at locations around the world