Purpose of the Role

The Data Engineer role is to design, develop, and implement robust data pipelines, and ETL processes to enable efficient extraction, transformation, and loading of data from diverse sources into our data warehouse. The Data Engineer will collaborate with cross-functional teams to understand business requirements and translate them into scalable data solutions. He/she will ensure data integrity, optimize data processing systems for performance and play a critical role in implementing data governance processes.

Key Job Responsibilities Specific duties include, but are not limited to:

1. Designing, developing, and implementing data pipelines and ETL processes to extract, transform, and load data from various sources into our data warehouse.
2. Collaborating with cross-functional teams to understand business requirements and translate them into scalable data solutions.
3. Optimizing and tuning data processing and storage systems for performance and scalability.
4. Implementing data governance processes and ensuring data quality and integrity.
5. Working with stakeholders to identify and address data-related issues, providing recommendations for improvement.
6. Keeping abreast of industry trends and best practices in data engineering, cloud technologies, and retail analytics.
7. Mentoring and providing technical guidance to junior members of the data engineering team.

*The above tasks and responsibilities are a summary of the typical functions of the job and may not be exhaustive of all possible responsibilities, tasks and duties of the role.

Requirements:

1. Bachelor's degree in Computer Science, Data Engineering, or a related field. Advanced degree preferred.
2. Proven experience as a Data Engineer in the retail industry, with a strong understanding of retail data models and workflows.
3. Expertise in Microsoft SQL Server (MSSQL) and experience with Azure cloud services, including Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
4. Demonstrated proficiency in designing and implementing complex ETL processes and data pipelines using SQL, Python, or other relevant programming languages.
5. Familiarity with data warehousing concepts, dimensional modeling, and data governance principles.
6. Experience with data visualization tools such as Power BI / Tableau / Qlik Sense is a plus.