Data Engineer

🔥 21 hours ago

🇫🇷 France – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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lemlist

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

lemlist is a comprehensive cold outreach platform that provides tools designed to help businesses reach their target audiences effectively. It includes features for email outreach, personal branding on LinkedIn and Twitter, lead generation, and seamless meeting booking. With its innovative solutions like email warm-up services and personalized content creation, lemlist empowers companies to enhance their reach and engagement, driving customer acquisition and building strong personal brands.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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