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Engaged Employer

Mondelez International

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4.2

based on 1k Reviews

Video summary

Proud winner of ABECA 2024 - AmbitionBox Employee Choice Awards

Top Rated Mid-Sized Company - 2024

Top Rated FMCG Company - 2024

30 Mondelez International Jobs

Senior Data Engineer

Mondel z International

4.2

based on 1k Reviews

8-13 years

Mumbai

1 vacancy

Senior Data Engineer

Mondelez International

posted 19d ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analysis Data Analytics Business Analytics Packaging Analytical Chemistry Informatica

+ 3 more

Job Description

Work in close partnership with the business leadership team to execute the analytics agenda
Identify and incubate best-in-class external partners to drive delivery on strategic projects
Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
Execute the business analytics program 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 senior leaders
Technical experience in roles in best-in-class analytics practices
Experience deploying new analytical approaches in a complex and highly matrixed organization
Savvy in usage of the analytics techniques to create business impacts

In This Role

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.

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 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.

Technical Requirements:

Programming: Python, PySpark, Go/Java
Database: SQL, PL/SQL
ETL & Integration: DBT, Databricks + DLT, AecorSoft, 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, PubSub, Dataflow, DataProc, 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.