What is your mission? 

You will provide the best service to our partner brands by performing these tasks:

Data Engineering & Architecture

• Design and develop scalable data pipelines for batch and real-time processing (Azure Data Factory, AWS Glue).

• Build and maintain ETL/ELT workflows for structured/unstructured data in OLTP, OLAP, and data lakes.

• Develop high-performance data models and ensure consistency and integrity across systems.

Data Warehousing & Business Intelligence

• Assemble and transform large datasets to meet functional and business requirements.

• Define and enforce enterprise-wide data governance and data quality standards.

• Design BI solutions using Power BI and similar tools for reporting, dashboards, and analytics.

Performance Optimization & Security

• Conduct root cause analysis for data issues and implement corrective actions.

• Optimize data storage and query performance in Synapse, Redshift, Athena, Microsoft Fabric.

• Apply data security best practices: encryption, access control, and compliance adherence.

Cross-Team Collaboration & Leadership

• Collaborate with Data Architects to define and execute the data strategy.

• Partner with Data Scientists and Analysts to support AI/ML pipelines and projects.

• Mentor junior engineers and champion data engineering best practices across teams.

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Who are we looking for?

• 7+ years of experience in data engineering, data modeling, or data architecture.

• Strong SQL expertise; hands-on with PostgreSQL, Oracle, Microsoft Fabric.

• Experience building ETL/ELT workflows using Azure Data Factory, Pentaho, AWS Glue, Kafka, etc.

• Deep understanding of OLAP vs. OLTP, data warehousing, and real-time ingestion.

• Hands-on experience with Azure (Synapse, Data Lake, Microsoft Fabric) and AWS (Redshift, RDS, S3, Athena, Kinesis).

• Familiarity with Python, Spark, or Java for data transformation tasks.

• Knowledge of event-driven architecture (Kafka), containerization (Docker), and version control (Git).

• Strong grasp of data governance, security best practices, and regulatory compliance.

• Experience with data visualization tools: Power BI, Tableau, Looker, or Quicksight.

• Exposure to AI/ML data pipelines using tools like SageMaker or Azure Machine Learning.

• Excellent analytical and communication skills, with a strong focus on data-driven decision-making.