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Data Engineer (Remote)

Remote: 
Full Remote
Contract: 
Full time
Experience: 
Mid-level (2-5 years)
Work from: 
Spain

Offer summary

Qualifications:

3-4 years experience as a Data Engineer using Spark, 1-2 years in Cloud environments, knowledge in data modeling and dashboard creation. Experience in Hadoop ecosystem, Spark, ETL, Azure technologies, PowerBI, and related tools. Optional but encouraged: additional experience in Azure and Spark technologies, Machine Learning, and Property Graphs..

Key responsabilities:

  • Designing pipelines for data extraction and transformation using Spark on Cloud platforms, primarily Azure. Building dashboards, industrializing scientific code, and optimizing service configurations for performance and reliability in multiple projects.
WayOps logo
WayOps Information Technology & Services Startup https://wayops.eu/
2 - 10 Employees
About WayOps
WayOps is a technology consultancy firm focused on the Digital, Data-driven and Cognitive Transformation of the enterprise. We characterize for offering a complete vertical portfolio including consultancy services, software solutions and professional services. Our expertise lies in technologies like Cloud, Big Data, AI, IoT or Devops and we specialize in designing, developing and industrializing E2E multidisciplinary solutions. We employ a team of certified professionals which uphold our corporate CLEAR values: Confidence, Leadership, Excellence, Adaptability and Resoluteness. Our project aims to provoke a paradigm change in the way our clients relate to technology, helping them in realizing that technology is not only a tool to execute business, but in times of Cloud, Big Data and AI, it is also the best tool to come up with new business models.
See more WayOps offers

Job description

En WayOps buscamos un perfil Data Engineer que quiera continuar su carrera profesional formando parte de un equipo Data & AI de primer nivel y trabajando en proyectos cloud con las últimas tecnologías.

La persona seleccionada participará en múltiples proyectos encargándose de construir pipelines orientadas a la extracción y transformación de los datos utilizando tecnología Spark en entornos Cloud, principalmente Azure. Además, desarrollará cuadros de mandos, industrializará código científico y optimizará la configuración de los servicios para mejorar el rendimiento y la fiabilidad. **

EXPERIENCIA & CONOCIMIENTOS**

El perfil a incorporar deberá contar con 3-4 años de experiencia como Ingeniero de Datos utilizando Spark, 1-2 años de experiencia en entornos Cloud, así como 1-2 años de experiencia en modelado de datos y elaboración de cuadros de mandos. Además, se valorarán conocimientos en Machine Learning, experiencia previa en industrialización de código científico y experiencia en resolución y gestión de incidencias en entornos productivos.

Se deberá aportar experiencia en las tecnologías:

  • Ecosistema Hadoop (HDFS, Map/Reduce, Spark, Hive)
  • Spark (RDDs, Dataframes, Python, SQL)
  • ETL (ER, Relational-model, Star-model, MDM)
  • Azure (Data Factory, Databricks, Storage, SQL Databases)
  • Analytics (PowerBI)
  • Herramientas (Git, Azure DevOps)

Además se valorará experiencia en tecnologías como:

  • Azure (Event Hubs, IoTHub, CosmosDB, ML Services)
  • Spark (GraphX & GraphFrames, Structured Streaming, Scala, Optimización)
  • Machine Learning (sklearn, mllib, h2o, tensorflow, keras)
  • Property Graphs (Neo4j+Cypher, Tinkerpop+Gremlin)

CONTRATACIÓN & UBICACIÓN

La contratación será como indefinido o autónomo en jornada completa. El trabajo se desarrollará en remoto aunque podría ser necesario realizar reuniones puntuales en nuestras oficinas. Banda salarial negociable en función de la modalidad de contratación y experiencia.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Information Technology & Services
Spoken language(s):
Spanish
Check out the description to know which languages are mandatory.

Hard Skills

Keras (Neural Network Library)ETOM (Enhanced Telecom Operations Map)TensorFlowApache TinkerPopPower BIData ModelingNeo4jGit (Version Control System)Azure Cosmos DBDashboardAzure Data FactoryAzure DevOpsAzure Event HubsIncident ManagementScikit-Learn (Python Package)Cloud InfrastructureMachine LearningCloud ServicesSparkrLiquid OxygenApache Hadoopmlpack (C++ Library)
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