Data Engineering & Analytics (DEA) has the mission to build the data pipelines and analytics for the Market Insight suite based on MIDT, Fqlogs and PAM, but as well as exploring new data sources, by leveraging big data technologies (Hadoop, Spark), combining different database systems (Impala, ElasticSearch) and operating in the cloud (AWS and soon Azure).

We are now looking for engineers already experienced or willing to learn and grow in data engineering and analytics.

Key accountabilities

As a data engineer in DEA, your role will be to:
• Identify data needs for business and product teams, understand their specific requirements for metrics and analysis
• Develop software: design, develop, test, debug, document and maintain scalable data-driven solutions
• Work with data scientists, data analysts, quality analysts and our business stakeholders to develop, implement and perfect features
• Improve the performances of our large-scale processing applications. and optimize their operational costs
• Industrialize software solutions: stability, monitoring, automation, operability, deployability, implementability
• Drive the collection of new data and the refinement of existing data sources, develop relationships with production engineering teams to manage our data structures
• Participate in the construction and evolution of our big data applications

Skills and Expertise expected:

• Experience in distributed Big data environments: Hadoop / Cloudera / EMR / Databricks
• Strong experience with Spark (Scala and/or Python)
• Experience working with large data sets
• Experience with cloud computing tools (AWS and/or Azure)
• Good experience in version control with Git and Linux shell
• Good understanding of databases technologies: relational, distributed, SQL/NoSQL
• Experience with column-store databases: Impala/Redshift
• Knowledge of statistics & machine learning is a huge plus, opening the door to advanced use cases.
• Exposure to BI tools, environments is a plus (Qlik, Tableau, …)