Data Proxy - Data Engineer

Key Skills

Analytical and Problem solving, Azure, Continuous Integration & Continuous Delivery - CI/CD, Data Architecture, Data Engineering, Data pipelines, Databricks, DevOps, Docker, Kanban, Kubernetes-K8s, Machine learning techniques, ProxySQL, PySpark, Python Programming, REST API, Scrum Agile Methodology, SQL

Job Description

The Tech & Data department (~200 employees across the globe) provides products, services, and support to all SCOR Group worldwide. Its 2 key challenges today are to successfully implement its new Target Operating Model (TOM), to be supported by an ambitious pluri-annual internalization plan to deliver innovative products and services to its clients. 

The Tech & Data organization is an Agile matricial organization relying on 4 pillars:

• Data and System Engineering, made of the following teams : Data Center of Excellence, Products and Systems Engineering and Enterprise Architecture 
• Management & Control (M&C) & Corporate Systems, made of teams supporting Crews and Transversal Functional Domains: Governance, T&D Operating Model Implementation, Security & Compliance, Financial Control, Sourcing & Vendor Management, Governance, and Processes
• Technical, made of teams dedicated to IT Operations, Network, Cloud, Workplace & Cloud Productivity Services
• Crews and Transversal Functional Domains

Crews are supported by Chapters (System Engineering, Architecture, DevOps, …) and both Technical and M&C-C teams are fully dedicated to the delivery of SCOR products, services and support. 

To support the ongoing transformation at Group level, a new Data Center of Excellence (CoE) has been created to drive innovation in data management, analysis and reporting for SCOR with the following objectives :

1. Design and Delivery of data products in an agile way following Tech and Data TOM
2. Define the strategic roadmap of SCOR data technical ecosystem to support Scor data ambition to become Data driven company
3. Support the roll-out of SCOR Data Governance
4. Be the reference on Data technical matters within the company. Data CoE will encompass the following Skills:

• ML Engineering
• Data Platform and tooling Expertise
• Data Engineering and Architecture
• BI engineering

As a member of the DataCoE, we are looking for a Data Engineer who will build, deliver and maintain data artefacts (data pipelines, data services, APIs…) within the Data CoE team.

The Data Engineer is responsible for :

• Building, delivering, maintain, documenting data artefacts or features (data pipelines, data services, APIs…) following state-of-the-art patterns (medaillon architecture, gitflow)
• Acting as SME and representative of Data CoE on core data engineering questions within squads he/she will be working with, and contributing to the global data engineering chapter

RESPONSIBILITIES

In the frame of the ongoing transformation at Group level, technology adoption and implementation are key success factors, as well as processes transition. As a member of the DataCoE, Data Engineer will build, deliver and maintain data artefacts (data pipelines, data services, APIs…) within the Data CoE team. He will work in close collaboration with products’ teams to develop new features linked to these products, especially features linked to :

• Data pipelining within or across multiple products
• Analytical and warehousing capabilities for data exploration, data science, BI
• Parallel calculation on big volumes of data

The Data Engineer is responsible for :

• Building, delivering, maintain, documenting data artefacts or features (data pipelines, data services, APIs…) following state-of-the-art patterns (medaillon architecture, gitflow)
• Acting as SME and representative of Data CoE on core data engineering questions within squads he/she will be working with, and contributing to the global data engineering chapter

He / She needs to:

• Be problem-solving oriented with strong analytical thinking
• Be autonomous and rigorous in the way he/she approaches technical challenges
• Advise on the architecture of end-to-end data flows
• Collaborate with various stakeholders (product owners, solution owners, data solution analysts, developers, technical leads, architects) to deliver data artefacts in a team spirit

Commit and bring his/her skills to contribute to the success of the Group

QUALIFICATIONS

Required experience & competencies

• +3 years of experience as a data engineering, data oriented mindset
• Proven experience in development and maintenance of data pipelines
• Good development practices (gitflow, unit tests, documentation…)
• Proven experience in agile projects (Scrum and/or Kanban)
• Knowledge of (Re)insurance industry and / or Financial Services is a plus
• Awareness on data management and data privacy topics

Technical Skills :

• Strong level in Python and Pyspark, ability to develop data pipelines under Databricks
• Strong level in SQL (knowledge of ANSI92 SQL, execution plan analysis)
• Good knowledge of parallelization, distributed programming techniques
• Good knowledge of datalakes environments and concepts (delta lakes, medaillon architecture, blob storage vs file shares…)
• Good knowledge in decisional data modeling (Kimball, Inmon, Data Vault concepts…) and associated good practices (slowly changing dimensions, point in time tables, chasm / fan trap management, change data capture management…)
• Knowledge of CI / CD pipelines (AzureDevOps, Jenkins, Artifactory, Azure Container Registry…)
• Knowledge of containers (Docker Compose, Kubernetes is a plus)
• Knowledge of REST API development (Flask, FastAPI, Django…)
• Knowledge of reporting tools is a plus (Tableau, Power BI…)
• Knowledge of streaming technologies is a plus (Kafka)

Behavioral & Management Skills :

• Strong analytical thinking, solution-oriented and force of proposal
• Capacity to navigate in a matrix and international environment ​
• Autonomy, rigorous mindset, curiosity
• Team player

Required Education 

• Bachelor's degree in computer science, software or computer engineering, applied math, physics, statistics, or a related field or equivalent experience