Data Engineering Lead - MSC
Mondelēz International · Mumbai Metropolitan Region
- On site
- Full-time
- $150,000 / year
- Mumbai Metropolitan Region
Job highlights
- Lead data engineering initiatives and analytics agenda.
- Design and build scalable cloud data solutions.
- Develop and maintain robust data pipelines.
- Ensure data quality and optimize storage.
- Collaborate with teams and stay updated on tech.
About the role
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:
- 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.
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 will you 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, 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, Power BI (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.
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 delicious range of 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
Department: Analytics & Modelling
Sub-Department: Analytics & Data Science
Key skills/competency
- Data Engineering
- Cloud Data Solutions
- Data Pipelines
- Data Quality
- SQL
- Python
- PySpark
- Databricks
- GCP
- AWS
Skills & topics
- Data Engineering
- Data Engineer
- Lead Data Engineer
- Python
- PySpark
- SQL
- Cloud Data Solutions
- Data Pipelines
- Databricks
- GCP
- AWS
- Azure
- ETL
- Data Warehousing
- Analytics
How to get hired
- Tailor your resume: Highlight experience with Python, PySpark, SQL, and cloud platforms (GCP, AWS, Azure) relevant to data engineering.
- Showcase impact: Quantify achievements in designing scalable data solutions and improving data quality.
- Prepare for technical questions: Review concepts like ETL, data warehousing, and specific cloud services mentioned.
- Demonstrate soft skills: Be ready to discuss problem-solving, communication, and adaptability with examples.
- Research Mondelēz: Understand their business, brands, and commitment to innovation in data.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary cloud platforms used for this Data Engineering Lead role at Mondelēz International?
- This role heavily involves GCP, AWS, and Azure cloud services. Proficiency in GCP (Big Query, GCS, Dataflow), AWS (S3, Redshift, Glue), and Azure (Azure Datalake Gen2, Azure Databricks) is crucial. Familiarity with their respective data services is expected.
- What programming languages are essential for the Data Engineering Lead position at Mondelēz?
- The key programming languages for this Data Engineering Lead role are Python and PySpark. Experience with Go or Java is also listed as beneficial. Strong SQL skills are also a must.
- What specific ETL and data warehousing tools are mentioned for this role?
- The job description specifies experience with DBT, Databricks + DLT, and various ETL tools like AecorSoft, Talend, Informatica/Pentaho/Ab-Initio, and Fivetran. Knowledge of data warehousing concepts such as SCD, Schema Types, and Data Marts is also required.
- How does Mondelēz International support international candidates for this Data Engineering Lead role?
- Mondelēz International offers some minimal support for candidates voluntarily moving internationally through their Volunteer International Transfer Policy. Within-country relocation support is also available.
- What soft skills are most important for a Data Engineering Lead at Mondelēz International?
- Key soft skills include strong problem-solving abilities for complex data challenges, effective communication to collaborate with various stakeholders, analytical thinking for insightful data analysis, meticulous attention to detail in development, and adaptability to stay current with evolving data engineering trends.
- What is the expected outcome of the business analytics program agenda at Mondelēz?
- The business analytics program agenda aims to develop custom models and algorithms to uncover signals, patterns, and trends that drive long-term business performance. It involves methodical execution to clearly communicate deliverables to stakeholders.
- Besides core data engineering, what supporting technologies are beneficial for this role?
- Beneficial supporting technologies include Graph Databases (like Neo4j), data cataloging tools (Erwin, Collibra), data quality tools (Ataccama DQ), and messaging/streaming platforms like Kafka and Airflow for workflow orchestration.