onsite
Data Engineer, Data Innovation - MNP
Data Engineer
Join a fast‑moving data innovation team as a Data Engineer, building scalable pipelines, data models, and cloud‑based solutions using Python, SQL, Azure, and Spark to drive digital transformation.
About the role
Key Responsibilities
- Design, develop, and maintain robust ETL pipelines that ingest, transform, and load data from multiple sources into cloud‑based data warehouses.
- Implement data models and schemas optimized for analytics and reporting, ensuring data quality and consistency.
- Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
- Leverage Azure services (e.g., Azure Data Factory, Synapse, Databricks) and Apache Spark for large‑scale data processing.
- Monitor, troubleshoot, and optimize performance of data workflows and storage solutions.
Requirements
- 3+ years of hands‑on experience building data pipelines using Python, SQL, and cloud platforms (preferably Azure).
- Strong understanding of data warehousing concepts, dimensional modeling, and ETL best practices.
- Proficiency with big‑data processing frameworks such as Apache Spark.
- Experience with Azure data services (Data Factory, Synapse, Databricks) or comparable cloud ecosystems.
- Ability to work autonomously, take ownership of deliverables, and collaborate effectively in a cross‑functional team.
Skills
pythonsqlazureapache spark