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Mondelez
Mondelez

Global snacking company

Sr. Data Engineer - MSC

职能数据工程
级别资深
地点Mumbai, India
方式现场办公
类型全职
发布1周前
立即申请

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 What you need to know about this position:

As a Senior 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.

What extra ingredients you will bring:

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 Storage: Ensure efficient data storage and retrieval for optimal performance.

 Collaborate and Innovate: Work closely with data teams, product owners, and stay updated with the latest cloud technologies and best practices.

Job specific requirements:

Programming: Python, Py Spark, Go/Java

 Database: SQL, PL/SQL

 ETL & Integration: DBT, Databricks + DLT, Aecor Soft, Talend, Informatica/Pentaho/Ab-Initio, Fivetran.

 Data Warehousing: SCD, Schema Types, Data Mart.

 Visualization: Databricks Notebook, PowerBI (Optional), Tableau (Optional), Looker.

 GCP Cloud Services: Big Query, GCS, Cloud Function, Pub Sub, Dataflow, Data Proc, Dataplex.

 AWS Cloud Services: S3, Redshift, Lambda, Glue, CloudWatch, EMR, SNS, Kinesis.

 Azure Cloud Services: Azure Datalake Gen2, Azure Databricks, Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics.

 Supporting Technologies: Graph Database/Neo4j, Erwin, Collibra, Ataccama DQ, Kafka, Airflow.

Soft Skills - 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.

Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy

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, bel Vita 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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关于Mondelez

Mondelez

Mondelez

Public

Mondelez International, Inc. is an American multinational confectionery, food, holding, beverage and snack food company based in Chicago. Mondelez has an annual revenue of about $26.5 billion and operates in approximately 160 countries.

10,001+

员工数

Chicago

总部位置

$84B

企业估值

评价

10条评价

3.6

10条评价

工作生活平衡

3.2

薪酬

3.5

企业文化

3.8

职业发展

2.8

管理层

2.9

65%

推荐率

优点

Supportive management/team

Good work-life balance and flexible hours

Excellent health benefits

缺点

Poor management communication/lack of support

High pressure/fast-paced work environment

Limited career advancement opportunities

薪资范围

35个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · MDS MTI Business Analyst

1份报告

$122,895

年薪总额

基本工资

$106,865

股票

-

奖金

-

$122,895

$122,895

面试评价

3条评价

难度

2.7

/ 5

时长

14-28周

录用率

33%

体验

正面 33%

中性 67%

负面 0%

面试流程

1

Application Review

2

Phone/HR Screen

3

Technical/Skills Assessment

4

In-Person/Final Interview

5

Offer Decision

常见问题

Technical Knowledge

Past Experience

Behavioral/STAR

Role-Specific Skills

Safety Procedures