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Data Engineer
2 weeks ago
What we do:
GMG is a global well-being company retailing, distributing and manufacturing a portfolio of leading international and home-grown brands across sport, everyday goods, health and beauty, properties and logistics sectors. Under the ownership and management of the Baker family for over 45 years, GMG is a valued partner of choice for the world's most successful and respected brands in the well-being sector. Working across the Middle East, North Africa, and Asia, GMG has introduced more than 120 brands across 12 countries. These include notable home-grown brands such as Sun & Sand Sports, Dropkick, Supercare Pharmacy, Farm Fresh, Klassic, and international brands like Nike, Columbia, Converse, Timberland, Vans, Mama Sita's, and McCain.
What will you do:
We are looking for a highly skilled Data Engineer with a strong foundation in data architecture and hands-on experience in enabling AI/ML workloads. You will be responsible for building & maintaining data pipelines, maintaining data lake environment on AWS databricks, and preparing high-quality, trusted data assets for machine learning models and advanced analytics.
Responsibilities:
Design, build, and manage ETL/ELT pipelines to support structured and unstructured data ingestion.
Build and maintain data lakes on Databricks
Ensure data quality, lineage, and governance using Unity Catalog.
Collaborate with Data Scientists to enable model training, deployment, and monitoring pipelines.
Transform raw data into feature stores and analytical-ready datasets.
Optimize data pipelines for large-scale ML training, experimentation, and inference
Implement CI/CD and data pipeline automation
Ensure robust data security and compliance across environments.
Technical Competencies:
5+ year of developement experience out of which 3+ on databricks
Must be hands-on with Python, AWS Glue, SQL
Knowledge of Delta Lake & Kafka, etc.
Knowledge of BigQuery is added advantage
Working knowledge of AWS, Azure, or GCP (experience with S3, EC2, Lambda, EMR, etc.)
Qualification and Experience:
Degree in Information Technology, Computer Science or equivalent
5+ years of total development experience, with 3+ on databricks