Data Platform Lead (Expert Databricks)
- Be problem-solving oriented with strong analytical thinking
- Be autonomous and rigorous in the way he/she approaches technical challenges
- Advise on the architecture and use of Databricks, and provide standard frameworks
- Collaborate with various stakeholders (data & analytics engineers, data architects, solutions owners, IT operation teams) to ensure that the best practices are followed on the platform
- Commit and bring your skills to contribute to the success of the Group
- Continuously drive the platform following a "platform-as-a-product" approach, by implementing new features to enhance it, in support of use cases and aligning with the target blueprint of SCOR's Data Strategy
- Be responsible for configuring and / or defining standard rights and access patterns to the platform.
- Implement Finops monitoring and alerting mechanisms.
- Optimize use of computational resources.
- Provide standardized, ready-to-use code templates.
- Enhance generic libraries to facilitate the ingestion, transformation, monitoring, alerting of data pipelines.
- Implement standardized frameworks for unit-testing, code quality checks and other CI frameworks to ensure operational excellence on the platform.
- Be a referent on Databricks technology.
- Provide guidance on implementation pattern, both from an applicative and an infrastructural point of view.
- Perform peer review and intervene when punctual expertise is required.
- Perform technological watch and ensure SCOR benefits from latest features of data platform technologies.
- Animate a community around Databricks.
- Ensure smooth integration with the rest of Data & IT ecosystem.
- +5 years of experience as a data engineer or data architect, data oriented mindset
- Proven experience on Finops implementation and platform administration
- Strong experience in development and maintenance of data pipelines
- Good development practices (gitflow, unit tests, documentation...)
- Knowledge of (Re)insurance industry and / or Financial Services is a plus
- Awareness on data management and data privacy topics
- Strong level in Python and Pyspark, ability to develop data pipelines under various platform with specific specialization in Databricks
- Strong level in analyzing DAGs and optimizing resources / codes
- Strong level in SQL (knowledge of ANSI92 SQL, execution plan analysis)
- Strong knowledge of parallelization, distributed programming techniques
- Strong knowledge of datalakes environments and concepts (delta lakes, medaillon architecture, blob storage vs file shares...)
- Good knowledge of CI / CD pipelines (AzureDevOps, Jenkins, Artifactory, Azure Container Registry...)
- Good knowledge of REST API development (Flask, FastAPI, Django...)
- Good knowledge of containers (Docker Compose, Kubernetes)
- Strong analytical thinking, solution-oriented and force of proposal
- Capacity to navigate in a matrix and international environment
- Autonomy, rigorous mindset, commitment
- Curiosity, interest to challenge
- Communication and ability to handover frameworks to other teams
- Team player
- Bachelor's degree in computer science, software or computer engineering, applied math, physics, statistics, or a related field or equivalent experience
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