Mission freelance Senior Data Engineer / Data Engineering Lead

Notre client dans le secteur Chimie recherche un/une Senior Data Engineer / Data Engineering Lead H/F

Description de la mission :

Job description – Senior Data Engineer / Data Engineering Lead

Context and objective of the mission

An organization is looking for a Senior Data Engineer / Data Engineering Lead to strengthen the Customer & Servicing (CAS) domain and support a growing data ecosystem used by multiple affiliated entities.

As the organization increasingly relies on analytics, reporting, Microsoft Fabric and data-driven decision making, the role focuses on building and operating reliable, scalable and maintainable data products and interfaces. The objective is to help establish strong data engineering practices and ensure high-quality data delivery for business, analytics and data science teams.

Success criteria

• Increase the reliability and stability of analytics data feeds
• Improve data quality and trustworthiness across the ecosystem
• Reduce incidents related to data interfaces and releases
• Establish sustainable engineering standards and best practices
• Enable analytics and reporting teams to consume high-quality and consistent data
• Strengthen the overall data engineering maturity of the CAS domain

Primary tasks and responsibilities

Data Engineering & Platform Development
• Design, develop and maintain robust data pipelines and integrations between operational systems, Microsoft Dynamics 365, Microsoft Fabric and downstream analytics platforms
• Gather, consolidate and prepare data required by BI, Analytics and Data Science teams
• Develop and maintain data architectures including Data Lake, Data Warehouse and Data Marts
• Design and implement scalable incremental loading strategies
• Define and implement data engineering standards, design patterns and best practices
• Ensure solutions are maintainable, scalable, secure and aligned with enterprise architecture principles
• Collaborate with architects, analysts, developers and data teams to design sustainable data solutions

Data Quality & Reliability
• Implement data quality controls and validation mechanisms across data pipelines
• Establish observability, monitoring and alerting capabilities for data interfaces and pipelines
• Define error handling, recovery and restartability mechanisms
• Improve operational robustness and reliability of production data products
• Anticipate and assess the impact of application changes and releases on data consumers
• Contribute to the definition and implementation of data contracts between source systems and analytics platforms

Analytics & Business Support
• Translate business needs into scalable technical data solutions
• Support reporting, analytics and data science initiatives by providing trusted and consistent datasets
• Create technical specifications and solution documentation
• Participate in troubleshooting, root cause analysis and continuous improvement initiatives
• Develop dashboards, monitoring reports and operational metrics where required

Leadership & Capability Building
• Act as the reference point for data engineering practices within the CAS domain
• Coach and mentor developers and analysts on data engineering principles and best practices
• Upskill teams on building stable, scalable and production-ready data interfaces
• Promote engineering excellence, automation and continuous improvement
• Contribute to defining the long-term data architecture roadmap for the domain

Secondary tasks and responsibilities
• Support project setup, deployment and assessment activities
• Participate in solution testing and quality assurance
• Document technical solutions and lessons learned
• Contribute to continuous improvement initiatives
• Assist in establishing development guidelines and operational procedures
• Collaborate with central Data, Architecture and Governance teams when required

Profile required

Technical profile
• Master’s Degree in Computer Science, Engineering or equivalent through experience
• Minimum 5 years of experience as a Data Engineer
• Experience designing and operating production-grade analytics and data platforms
• Experience in data integration, ETL/ELT and cloud-based data architectures
• Experience with large-scale enterprise environments and multiple stakeholders

Mandatory skills
• Strong SQL knowledge
• Strong Python development skills
• Experience with Spark, Hive or similar big data technologies
• Strong experience with Microsoft Azure data services and/or AWS data platforms
• Experience with Microsoft Fabric, Synapse, Data Factory or equivalent cloud data platforms
• Experience with ETL/ELT tools and orchestration frameworks
• Experience designing reliable data pipelines and analytics interfaces
• Experience implementing monitoring, observability and operational support mechanisms
• Strong understanding of data quality management practices
• Understanding of CI/CD and DevOps principles applied to data platforms

Nice to have
• Knowledge of Data Vault and dimensional modelling (Star Schema)
• Experience with Databricks
• Experience with Power BI
• Experience supporting machine learning and advanced analytics platforms
• Knowledge of data governance concepts and data contracts

Non-technical profile
• Strong analytical and problem-solving mindset
• Excellent communication and stakeholder management skills
• Ability to work autonomously and manage multiple priorities
• Customer-oriented and results-driven
• Strong ownership and accountability
• Structured and organized approach
• Team player with coaching and mentoring capabilities
• Continuous improvement mindset

Methodology / certification requirements
• Master’s Degree in Computer Science or equivalent through experience
• 5+ years of experience in a similar role

Expected deliverables
• Robust and maintainable data pipelines and integrations
• Technical specifications and solution documentation
• Dashboards, monitoring reports and operational metrics where required
• Development guidelines, operational procedures and documented lessons learned

Compétences / Qualités indispensables :

Data engineering leadership, SQL, Python, Cloud data platforms (Microsoft Fabric, Azure, AWS), ETL/ELT and scalable data pipelines, Data quality, monitoring and observability

Compétences / Qualités qui seraient un + :

Informations concernant le télétravail :

Oui — 3 jours/semaine