Senior Data Engineer

Join

PARFOIS Data Intelligence

and play a key role in shaping the future of our global data platform.

We are looking for a

Senior / Lead Data Engineer

to drive the evolution of our Data Engineering capabilities, combining hands‑on engineering, technical leadership, architecture design and data platform modernization.

You will be responsible for designing and implementing scalable, reliable and secure data solutions that support analytics, operational reporting, advanced data initiatives and business decision‑making across a global retail organization.

This role will serve as the technical reference for the Data Engineering area, driving architectural decisions, establishing best practices and supporting the technical development of the team, while ensuring the continuous evolution of our Azure and Snowflake‑based data ecosystem.

MAIN RESPONSIBILITIES:

Act as the technical reference for the Data Engineering team, promoting best practices, technical excellence and knowledge sharing.

Define and evolve the organization's data architecture, ensuring scalability, performance, security and maintainability.

Design, develop and maintain robust ETL/ELT processes and data pipelines across the enterprise data platform.

Develop scalable data products that support reporting, analytics and advanced data initiatives.

Lead the evolution of our Cloud Data Platform, with a strong focus on Azure and Snowflake technologies.

Integrate data from multiple sources, including databases, APIs, SaaS platforms, files and streaming technologies.

Optimize existing processes and data pipelines, improving performance, reliability and operational efficiency.

Implement monitoring, observability, logging, auditing and data quality frameworks.

Define development standards, architecture guidelines, version control practices and engineering processes.

Evaluate and define technical solutions, balancing performance, scalability, cost and maintainability.

Lead the implementation and evolution of CI/CD practices and deployment processes for Data Engineering components.

Collaborate closely with Data Analytics teams, business areas, IT and other stakeholders to support data‑driven decision‑making.

Support the technical growth of team members through mentoring, coaching and technical guidance.

Contribute to the long‑term Data Engineering roadmap, helping modernize the platform towards cloud‑native and scalable architectures.

Promote Data Governance principles and ensure data quality, consistency and trustworthiness across the platform.

REQUIREMENTS (MUST HAVE):

Solid experience in

Data Engineering , ideally 5+ years.

Experience in technical leadership, architecture definition and team guidance.

Strong knowledge of

SQL

and relational databases, particularly SQL Server.

Solid experience developing

ETL/ELT

solutions and data pipelines.

Experience with

Cloud Data Platforms , preferably

Microsoft Azure .

Experience with

Snowflake

or other Cloud Data Warehouse platforms.

Knowledge of

Data Warehouse, Data Lake and Data Platform architectures .

Experience with orchestration tools such as

Airflow

and/or

Azure Data Factory .

Experience with

Git and CI/CD

practices, ideally Azure DevOps.

Ability to analyse complex problems, identify bottlenecks and optimise data processes.

Ability to define technical standards and software engineering best practices.

Strong communication skills and ability to engage with different stakeholders.

NICE TO HAVE:

Knowledge of

Python and SQL

applied to Data Engineering.

Experience with

Kafka, Streaming and Event-Driven Architectures .

Experience with

Azure Functions, Azure Blob Storage

or other Azure services.

Experience with

Power BI, SSAS

and integration between Data Engineering and BI platforms.

Knowledge of

Data Governance, Data Quality and Data Observability .

Experience migrating data platforms from

On-Premise to Cloud

environments.

Knowledge of modern data architectures, namely

Lakehouse

and distributed processing technologies.

Experience working in

Agile/Scrum

environments and backlog management tools.

WHAT WE OFFER:

The opportunity to shape and influence the evolution of a modern enterprise data platform.

Participation in high-impact projects within a global retail organization.

Exposure to a modern technology stack, including Azure, Snowflake and advanced Data Engineering practices.

Integration into a highly skilled and collaborative Data Intelligence team.

Continuous learning and professional development opportunities.

Autonomy to influence architectural decisions and technical direction.

Hybrid working model and a strong focus on innovation and continuous improvement.

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