Data Engineer

As a Data Engineer , you will play a vital role in bridging the gap between data engineering and analytics to deliver actionable insights that drive strategic decisions. You will design, build, and optimize scalable data pipelines, data models, and dashboards that enable business teams to make data-driven decisions with confidence

You’ll collaborate closely with cross-functional teams—including marketing, sales, and operations—to transform raw data into valuable business intelligence, particularly in the fast-paced beauty and FMCG industries where data-driven insights are key to consumer understanding and growth.

Key Responsibilities

• Design, develop, and maintain data pipelines and ETL processes using Airflow , Python , and Google Cloud Platform (GCP) tools.
• Build and optimize data warehouses in BigQuery , ensuring data integrity, scalability, and performance.
• Develop and maintain Power BI dashboards to provide key business metrics, trend analysis, and performance insights.
• Collaborate with business stakeholders to understand analytical needs and translate them into efficient data models and solutions.
• Implement data modeling best practices (star / snowflake schemas) to support analytics and reporting.
• Apply query optimization and performance-tuning techniques to enhance system efficiency.
• Ensure high data quality, consistency, and governance across data systems.
• Work cross-functionally with marketing, sales, and finance teams to provide insights that support campaign performance, product launches, and market expansion.

Requirements

Preferred Qualifications

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