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Mondelēz International

Sr. Data Engineer

Posted An Hour Ago
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Hybrid
Mumbai, Maharashtra
Senior level
Hybrid
Mumbai, Maharashtra
Senior level
Design and build scalable cloud-based data solutions, develop ETL pipelines for warehouses and data lakes, enforce data quality, optimize processing and storage, collaborate with data and product teams, and mentor other engineers. The role requires expertise in Python, PySpark, SQL, Databricks, AWS services, data modeling, medallion architecture, and scheduling technologies.
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Job Description
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.
How you will contribute
You will:
  • Execute the business analytics agenda in conjunction with analytics team leaders
  • Work with best-in-class external partners who leverage analytics tools and processes
  • Use models/algorithms to uncover signals/patterns and trends to drive long-term business performance
  • Execute the business analytics agenda using a methodical approach that conveys to stakeholders what business analytics will deliver

What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
  • Using data analysis to make recommendations to analytic leaders
  • Understanding in best-in-class analytics practices
  • Knowledge of Indicators (KPI's) and scorecards
  • Knowledge of BI tools like Tableau, Excel, Alteryx, R, Python, etc. is a plus

More about this role
As a Data COE Sr. Data Engineer, you will have the opportunity to design and build scalable, secure, and cost-effective cloud-based data solutions. You will develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes, ensuring data quality and validation processes to maintain data accuracy and integrity. You will ensure efficient data storage and retrieval for optimal performance, and collaborate closely with data teams, product owners, and other stakeholders to stay updated with the latest cloud technologies and best practices.
Experience: Data Engineering: 6 to 10 years with high expertise in required tech stack.
Role & Responsibilities:
  • Design and Build: Develop and implement scalable, secure, and cost-effective cloud-based data solutions.
  • Manage Data Pipelines: Develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes.
  • Ensure Data Quality: Implement data quality and validation processes to ensure data accuracy and integrity.
  • Optimize Data Processing & Storage: Ensure efficient data processing of pipelines & data storage for optimal retrieval performance.
  • Collaborate and Innovate: Work closely with data architects, data modelers, data product managers, and stay updated with the latest cloud technologies and best practices.
  • Mentoring: Guide & groom associate data engineers & data engineers (external/internal) to ensure timely deliverables fulfilling all data engineering guidelines & standards.

Technical Requirements:
  • Programming: Python, PySpark, SQL
  • ETL & Integration: Databricks (LDP, Lakeflow Connect, Notebooks), AecorSoft/DataSphere
  • Data Warehousing: SCD Types, Fact & Dimensions, Star Schema, ETL
  • Data Modeling: Dimensional modelling understanding, Erwin tool (Optional)
  • Medallion Architecture: Bronze, Silver, Gold (Databricks Medallion Architecture)
  • AWS Cloud Services: S3, Lambda, EC2, Glue, Redshift
  • GenAI exposure: Genie/Kiro/Gemini etc.
  • Scheduling Technologies: Lakeflow Jobs, Airflow
  • Visualization (Optional): PowerBI (Optional), GenBI (Optional)

Soft Skills:
  • Problem-Solving: The ability to identify and solve complex data-related challenges.
  • Communication: Effective communication skills to collaborate with Engineering Leads, Data Product Managers, Data Modeler, Data 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.

No Relocation support available
Business Unit Summary
At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about.
We have a rich portfolio of strong brands globally and locally including many household names such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum.
Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen-and happen fast.
Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Job Type
Regular
Analytics & Modelling
Analytics & Data Science

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