Descripción y requisitos
As a Digital Merchandising Data Engineer, reporting to the Performance and Insights Senior Manager. Work type model is Hybrid.
What You'll Do:
You'll develop ETL pipelines that integrate digital merchandising data from many sources
You'll improve data processes to handle large-scale structured and unstructured data using tools like Apache Airflow, AWS Glue, Azure Data Factory, or DBT.
You'll ensure data accuracy, consistency, and reliability across merchandising platforms.
You'll automate data ingestion and workflows, enhancing the team's analytics capabilities.
You'll collaborate with the Data Analyst, IT and Data Governance teams to maintain compliance and data quality standards.
You'll implement and refine data governance practices,
You'll apply best practices for data normalisation, indexing, and partitioning to boost system performance.
You'll scale workflows as our digital merchandising data volume grows.
You'll manage and enhance insightful dashboards in Looker (preferred), Power BI, or Tableau to Experience communicating updates and resolutions to customers and other partners digital merchandising Measurements.
You'll troubleshoot and improve dashboards for performance.
Experience And Qualifications You Bring:
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related fields.
3+ years of proven experience in ETL development, data transformation, and database management.
SQL skills (complex queries, indexing, and optimization).
Familiarity with Python or R for analytics and automation tasks.
Experience with ETL tools (Apache Airflow, DBT, AWS Glue, Fivetran, Informatica).
Experience with cloud environments (AWS, Azure, or Google Cloud) and data warehouses (Redshift, Snowflake).
Familiarity with visualisation tools such as Power BI, Tableau, or Looker.
Understand data governance principles, security, and compliance.
Experience working with large disparet datasets
Knowledge of APIs for digital merchandising and inventory management.