Data Engineering Lead - Finance
Mondelēz International (company site, opens in a new tab)MumbaiOn-siteDirect career pageEst. 18–32 LPA
Posted 11h ago
Reach people at Mondelēz International
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Mondelēz International you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design and implement scalable, secure, cost-effective cloud-based data solutions.
- Lead and manage a team of data engineers to deliver data engineering projects on time and according to standards.
- Develop and maintain ETL data pipelines ensuring data quality, validation, and optimized data storage and retrieval.
Minimum Requirements
- Proficient in Python, PySpark, SQL; experience with Databricks (mandatory).
- Experience with cloud platforms (AWS preferred: Glue, Redshift, Lambda, EMR, Athena).
- Familiarity with data warehousing concepts such as SCD Types, Fact & Dimensions, Star Schema.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in leading and managing external/internal data engineering teams for timely deliverables.
- Strong background in cloud-based data engineering solutions and ETL pipeline design, especially on AWS and Databricks.
- Familiar with Medallion Architecture and integration of GenAI technologies (Gemini/Genie/Kiro) is a plus.