Senior Data Engineer

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Mondelēz International

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2012

👥 B2C

🛒 Retail

B2C • Retail • Food

Mondelēz International is a global leader in the snacking industry, well-known for its iconic brands like Cadbury, Oreo, and Toblerone. The company is involved in producing and marketing a wide range of chocolate, biscuits, candy, and other snacks, which are available to consumers across the world. Mondelēz is committed to corporate governance, sustainability, and making a positive impact on communities through initiatives in diverse areas like environmental sustainability and diversity, equity, and inclusion. The company operates in various sectors, including manufacturing, marketing, and supply chain management, and has a significant presence in multiple countries.

📋 Description

• Design and implement scalable, secure, and cost-effective cloud-based data solutions • Develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes • Implement data quality and validation processes to ensure data accuracy and integrity • Ensure efficient data storage and retrieval for optimal performance • Collaborate closely with data architects, data modelers, and product owners • Create & lead a team of data engineers (external/internal) to ensure timely deliverables fulfilling all data engineering guidelines & standards

🎯 Requirements

• 3+ years of experience in data engineering • Programming: Python • Database: SQL, PL/SQL, Postgres SQL, Big Query, Stored Procedure / Routines • ETL & Integration: AecorSoft / Datasphere, DBT, Databricks (Optional) • Data Warehousing: SCD Types, Fact & Dimensions, Star Schema • Data Modeling: Erwin (Optional) • Medallion Architecture: Bronze, Silver, Gold, Platinum • GCP Cloud Services: Big Query, GCS, Cloud Function/Run, GKE • Supporting Technologies: Airflow (Composer), Automic • Visualization (Optional): PowerBI (Optional), Tableau (Optional) • Problem-Solving: The ability to identify and solve complex data-related challenges • Communication: Effective communication skills to collaborate with Product Owners, analysts, and stakeholders • Analytical Thinking: The capacity to analyze data and draw meaningful insights • Attention to Detail: Meticulousness in data preparation and pipeline development • Adaptability: The ability to stay updated with emerging technologies and trends in the data engineering field.

🏖️ Benefits

• No Relocation support available