When you come to work at Davidson, you won’t just be joining a group of 3,000 consultants in 6 countries and 2 continents, you’ll be joining “the” company named by its employees as Great Place To Work France and Europe for four years, as well as the largest B Corp in France.
“B Corps” form a community of companies that have decided that, rather than being the best in the world, they’ll be the best *for* the world.
Our growth is based on strong principles:
Deep respect for all our stakeholders: consultants, customers and suppliers, because although work can’t “buy happiness”, it can “cause unhappiness”. We’re therefore committed to listening, acting honestly and promoting equality (Women / Men but not only).
A minimum environmental footprint and a maximum societal footprint. This is why, aside from the assignments you’ll be working on, you’ll also have the chance to contribute to the projects Davidson supports: international solidarity assignments (with Planète Urgence), supporting students from disadvantaged backgrounds (with Article 1) and investing in start-ups that develop innovative solutions.
Adhocratic management based on implementing “horizontal company” and “tribal management” principles.
One important point about the latter: well-being at work is a luxury you need to have as a “solid” company. For the Davidson teams, this means marrying initiative, commitment and professionalism, as “without work, talent is just a dirty habit”. It drives us to recruit components that are better than we are. In a classic hierarchical organisation, it can be beneficial to have an army of people who work for you. In an adhocracy, that doesn’t work.
Mission / Profile
Davidson’s Infrastructure Unit is looking for a database specialist to support its full range of internal and customer projects. This will involve work not only on “traditional” databases but also on next-generation architectures. In fact, one of your primary duties right now will be to migrate the former to the latter.
Your daily tasks will include: :
- Researching and analysing DBMS requirements
- Architecture proposals (initial design or future developments): cloud and/or on-premise
- Analysing operability issues
- Specifying housekeeping tasks: alarms, scheduling, backups
- Specifying and implementing tools for standardising, automating and securing production
- Scheduling and monitoring project phases
- Integrating new servers / databases
- Analysing and managing operational incidents, performing data recovery or rollbacks and handling maintenance operations
- Producing lessons-learned documents and procedures (operations, incidents, etc.)
- Implementing and tracking performance indicators
- Day-to-day platform monitoring
- Migrations of DBMS versions
- Technical support for users (developers, end customers)
Skills (pre-existing or to be acquired)
- You will have a postgraduate degree and some initial successful experience in database architecture and operation
- And, obviously, some of the following skills: SQL, Oracle, SQL Server, MySQL, PostgreSQL, Hadoop, Perl, Shell, Linux
- Analytical ability
Description of the segment's business
Today, data is a strategic asset that is central to the digital transformation of businesses and acts as the bedrock for creating multiple new services. Davidson’s unique data expertise enables it to deliver an end-to-end service for its customers, whether they’re data-driven or are “simply” looking to get the most out of their data.
Our business lines:
- Support for implementing a data strategy
- Big data architecture
- Data visualisation
- Data science
Our technical environment:
- Infrastructures & Storage: Cloud (AWS, Azure, Google Cloud Platform), Cloudera,
- MapReduce, Hortonworks, mongoDB, Hadoop, Cassandra, Splunk, Redis, CouchDB
- Data-processing: Spark, Scala, Kafka, Logstach, Elasticsearch, Hive, Storm, Flink
- Analytics: R, Python, SPSS&SAS, TensorFlow, Sickit learn
- Dataviz: grafana, dataiku, kibana, Tableau, Qlik, JS proprietary tool
- DevOps & containers: Docker, puppet, Jenkins, Sonar, Openshift, Kubernetes, Ansible
- Fields: machine learning, deep learning