Market Technologist Engineer
Procter & Gamble
Madrid, Spain
hace 2 días


Do you want to use your AnalyticSkills and Strategic Thinking to drive Billion Dollar Brands? Are you lookingfor a dynamic experience that puts together Technical Analysis and BusinessIntelligence?

Ifyes, apply here : What :

What :

Leader of dataapplication, integration and data modeling & business processtransformation, Big data modeling.

Business Need : Become a BIG DATA centric CPG Companyand turn data into a competitive advantage for sustainable and profitablegrowth ’data driven problem solver’’


  • Establishing THE Data hub and integrate different data systems / platforms
  • Understand new data sets and business opportunities to simplify use of platforms
  • Data Understanding and strong commitment to protect data privacy, GDPR, Info Sec for company
  • New Big data models : integrate data to accelerate performance marketing
  • Behaviour : Be and become the dataprofessionals who prepare the big data infrastructure and apply Data Science.Required a good understanding of statistics, be familiar with statisticaltests, distributions, maximum likelihood estimators, etc.

    This will also be thecase for machine learning, but one of the more important aspects of thestatistics knowledge will be understanding when different techniques are (oraren’t) a valid approach.

    Statistics is important at all company types, butespecially data-driven companies where stakeholders will depend on your help tomake decisions and design / evaluate experiments.

    They are software engineerswho design, build, integrate data from various resources, and manage big data,data-driven problem-solver.

  • Then, they write complex queries on that, make sureit is easily accessible, works smoothly, and their goal is optimizingtheperformance of their company’s big data ecosystem;
  • and it’s really importantto know how to deal with imperfections in data. They might also run some ETL(Extract, Transform and Load) on top of big datasets and create big datawarehouses that can be used for reporting or analysis by data scientists.

    Beyond that, because Data Engineers focus more on the design and architecture,this resource should have to know machine learning or analytics for big data.


    Skills : Programming Skills, Statistics, MachineLearning, Multivariable Calculus & Linear Algebra, Data Wrangling, DataVisualization & Communication, Software Engineering, Data Intuition

    Methods : Hadoop, MapReduce, Hive, Pig, Datastreaming, NoSQL, SQL, programming, AWS, R or Python, and database queryinglanguage like SQL.

    Tools : DashDB, MySQL, MongoDB, Cassandra, Knime

    Location : preferably MadridYears of experience : -

    Location : Madrid, Spain

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