The Senior Data Engineer designs and builds data foundations and end-to-end solutions to maximize value from data. This role promotes a data-driven culture across the organization not only within IT teams but also across business stakeholder communities.

The Senior Data Engineer acts as a Subject Matter Expert (SME), responsible for designing and building scalable data solutions while mentoring junior engineers. The role also drives the translation of business vision and data strategy into effective IT solutions and successful delivery.

Roles and Responsibilities :

- Design and build scalable data foundations and end-to-end data solutions.

- Drive data-driven thinking across business and IT stakeholders.

- Convert business vision and data strategy into implementable technical solutions.

- Mentor and guide junior data engineers.

- Act as Subject Matter Expert (SME) for Data Analysis and Design.

- Lead the rollout and embedding of Data Foundation initiatives aligned with key business programs.

- Coordinate change management, incident management, and problem management processes.

- Present reports, insights, and findings to key stakeholders.

- Improve implementation efficiency and effectiveness across pilots and future projects to :

1. Minimize costs

2. Increase speed of implementation

3. Maximize value delivery

Key Characteristics :

- Strong technology expert with continuous learning mindset.

- Deep expertise in data engineering and related technology domains.

- Naturally curious and capable of understanding problems from multiple dimensions.

- Strong communication skills able to interact effectively with both technical teams and business leaders.

- Trusted and respected by leadership and peers.

Mandatory Skills :

- Expert-level proficiency in cloud platforms, including AWS, Azure, and SAP, with strong capabilities in ELT and data modeling.

- Solid hands-on experience in data integration, ingestion, manipulation, and processing across large-scale data systems.

- Strong working knowledge of version control and DevOps practices using tools such as GitHub, GitHub

Actions, and Azure DevOps.

- Extensive experience with modern data engineering and processing tools, including Azure Data Factory, Databricks, SQL DB, Synapse, and Stream Analytics.

- Familiarity with AWS data ecosystem tools such as Glue, Airflow, Kinesis, and Redshift for building scalable data pipelines.

- Experience with code quality, testing, and monitoring tools such as SonarQube and PyTest.

Good to Have (Optional Skills) :

- Experience in project management and running Scrum teams.

- Experience with BPC and Planning tools.

- Exposure to working with external technical ecosystems.

- Experience with MKDocs documentation.