ARQUITECTO SENIOR BIG DATA

Madrid
€40000 - €55000 per annum + BENEFITS

ARQUITECTO SENIOR BIG DATA

40.000-50.000

MADRID

Si eres un Arquitecto Big Data con amplia visión de negocio, y te gustaría incorporarte a una empresa que te brinde la oportunidad de formar parte de proyectos de primer nivel utilizando las últimas tecnologías, ¡tengo algo que puede interesarte!

LA EMPRESA:

Nuestro cliente, consultora tecnológica con amplio prestigio en el sector, trabaja con clientes de primer nivel dentro de diferentes sectores como puede ser el bancario, retail, energía, telecom.

Ha experimentado en los últimos años un gran crecimiento y antes las expectativas de que ello vaya a más busca ahora incorporar en sus oficinas de Madrid a un amplio número de expertos Big Data.

Se trata de una de las compañías más atractivas para trabajar en entornos Big Data dentro del panorama nacional, no solo por la repercusión de los proyectos en los que participa, si no también por la oportunidad de progresar en una empresa en expansión.

EL ROL:

Se requiere un perfil muy técnico, con amplia visión de negocio y con experiencia gestionando equipos - trabajarás junto al resto de ingenieros y desarrolladores.

Como Arquitecto Senior trabajarás en proyectos relacionados con arquitecturas Big Data y microservicios: diseño de la arquitectura, implementación, desarrollo, pruebas de concepto.

EXPERIENCIA:

-Haber trabajado con metodologías Ágiles.

-Sólida experiencia comercial desarrollando e implementado soluciones Big Data utilizando herramientas como Spark, Scala, Kafka, Hadoop, Java, Impala.

-Experiencia trabajando en el cloud: AWS, Big Query, Azure.

-Background como desarrollador.

BENEFICIOS:

-Salario competitivo + Beneficios.

-Posibilidad de progresión.

-Oficina moderna.

-Ambiente dinámico e internacional.

CÓMO APLICAR:

Para aplicar a esta posición, pincha en este enlace o contacta conmigo directamente en Ana García - Harnham

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34246-03/AG
Madrid
€40000 - €55000 per annum + BENEFITS
  1. Permanent
  2. Big Data

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Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

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Do you like breaking things down to see how they work? Do you want to build something that helps solves problems and can make lives better? Are you a puzzle solver curious about the world around you with a knack for mathematics? Do you prefer to work behind the scenes or front of stage? If you want to be the person behind the curtain, then this is your year. The year of the Data Engineer is here.  In last week’s article, we talked about Data Engineer as the unsung hero of the data science world and briefly touched on route to the role of engineer. Though experience supersedes education, you do need the basics – a bachelor’s degree in computer science, data science, applied math, physics, statistics, software/computer engineering which can lead to a Master’s in Data Engineering and to cement your knowledge – fellowships and professional organisations are now available around the world. In today’s article, we’ll cover a few options.  Lay Your Educational Foundation Computer Science, Data Science, and Engineering programs abound in university today, but no school can really teach big data skills. It’s too focused. Most schools today offer general purpose tech education with a focus on web development or backend systems. And here begins that Catch-22. Though experience supersedes education, you still need a framework from which to build.  More often than not, if you type Data Engineer into Google looking for education programs, you’ll get undergrad opportunities for Data Science. However, that’s not to say a Bachelor’s in Data Science can’t lead you to a Master’s in Data Engineering. So, how do you get from point A to point B? Here are a few suggestions:  Beef up your skills with specific certifications for the languages businesses need – Scala, Python, and Java  Take courses in data engineering technology: Hadoop, Spark, AWS, GCP, Azure etc.   Join a professional organization for Data Engineers such as The Data Warehousing Institute  (TDWI) or the Institution of Engineering and Technology (IET) – here you’ll find articles, resources, and a network of mentors ready to offer advice and suggestions.  Apply for a fellowship  with ASI Data Science – an 8-10 week intensive project with one of their partner companies to solve real-world business problems using Data Science or Data Engineering skills. If you’re a postgrad or higher, this a perfect opportunity to build your portfolio.  Boost Your Data Engineering Resume with These Tips In the world of data engineering, it’s important to highlight the details. Be specific: Companies will be more interested in interviewing you if you can clearly outline why/what you have used different technology for. Keep this punchy and concise, and outline your in-put with said technologiesOutline projects you’ve worked on Detail the technologies you’ve used  David Bianco, a Data Engineer with Urthecast, offers the following advice to data engineering students. Be fluent in the languages and tools you use to get the job Understand the concepts behind what you’re doing Get involved with a community – meetup.com, hackathons, and other groups in your area are great places to get started.  If you’re interested in switching your career  to Big Data, check out Jessen Anderson’s new e-book, The Ultimate Guide to Switching Careers to Big Data -- Upgrading Your Skills for the Big Data Revolution.  Your Turn: Route to the Role of Data Engineer Our data driven world moves at lightning speed and it can be hard to keep up. If you’re a Data Engineer, we want to hear your story.  What was your route to the role? What kind of cross-training programs might businesses and schools employ for future Data Engineers?    What other backgrounds are we overlooking as businesses seek to find and engage this most critical role within their data science teams?    What can we, as recruiters do to engage qualified candidates ready for their next role in the world of data and analytics? 

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