Python Job: Databricks Machine Learning Engineer

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.

You will provide technical contributions to the data science process. In this role, you are the internally recognized expert in data, building infrastructure and data pipelines/retrieval mechanisms to support our data needs

How you will contribute

You will:

• Operationalize and automate activities for efficiency and timely production of data visuals
• Assist in providing accessibility, retrievability, security and protection of data in an ethical manner
• Search for ways to get new data sources and assess their accuracy
• Build and maintain the transports/data pipelines and retrieve applicable data sets for specific use cases
• Understand data and metadata to support consistency of information retrieval, combination, analysis, pattern recognition and interpretation
• Validate information from multiple sources.
• Assess issues that might prevent the organization from making maximum use of its information assets

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Extensive experience in data engineering in a large, complex business with multiple systems such as SAP, internal and external data, etc. and experience setting up, testing and maintaining new systems
• Experience of a wide variety of languages and tools (e.g. script languages) to retrieve, merge and combine data
• Ability to simplify complex problems and communicate to a broad audience

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Deep understanding of Databricks or Apache Spark , running Python on Apache Spark through PySpark , MLOps practice through MLFlow
• Good understanding of Google cloud applications likes of Google Big Query, Google Cloud Storage
• Expertise in ETL activities, data movements across environments, data maintenance, and data management
• To promote cross-team collaboration: Sharing and enforcing ‘good practices’ in code standardization, maintenance, data creation
• Problem resolution mindset: A natural inclination toward solving technology problems such as code debugging, users access issue resolution, root cause analysis of system outage
• Support Forecasting Solution Implementation for market for demand modelling in DataBricks & Spark and Model Forecast Improvement activity.
• Broad understanding of the challenges a data scientist faces to run analytical machine learning jobs and
• Owns responsibility of assigning and deploying clusters to ensure optimal run time of forecasting models

More about this role

What you need to know about this position: The specialist will be responsible for the system level ownership of the delivery of forecast every cycle.

• Databricks ownership : You will own end to end Databricks solution including dev/prod separation, monitoring of the cost and efficiency
• Maintaining system architecture: Co-ordinating and ensuring best practice for System level tasks such as : naming convention (table, column), structure of the library as per the best practice
• Create code blueprints: navigate the forecasting team in the performance optimization on Spark cluster, guide on best libraries, code blueprints
• Scaling and cost control : Optimize the cluster scaling (horizontal and vertical) against the cost
• Manage and Govern code : Own the responsibilities of coding best practice by individual data scientists and implement principles of interoperability, modularity and scalability
• Overall ETL process ownership : Code review / Quality of the code management, Optimization (including Google Big Query, Spark), Code merge from different modellers, Release preparation
• Collaborate with DS and Project / Enterprise IT: Need to represent Data science team in technical discussion with (upstream and downstream of the platform) IT team and operationalize the code from ‘experimental’ zone to ‘deployment’
• On-boarding new country : Depending on the complexity of the process and structure of the data this role will ensure sustainability of the overall process and orchestrate the change
• Version Upgrade : In case of impact on existing set-up (code, jobs) due to version upgrade, the role will be assessing the impact and fix it (occasional)
• Job load managing: at the system level decide the number of parallel jobs and impact on modelling approach/ data change

No Relocation support available

Business Unit Summary

Mondelez México has been in the country since 1927 and currently employs 6,000 wonderful people. Our diverse portfolio includes iconic and mouth-watering global brands such as Trident , Oreo , Philadelphia , and local jewels like Clorets and Bubbaloo . We are leaders in the making of cream cheese, powdered beverages and confections—in fact, we make seven out of every 10 chewing gums consumed by Mexicans. Our growth is supported by our cutting-edge manufacturing facilities, such as our Puebla Plant and Nuevo León HUB, which are the largest gums, candies and biscuits factories in the world in terms of volume. You can buy are products in 900,000 places in Mexico. We are also home to one of the 11 technology centers Mondelez International has worldwide, a specialized gum and candy facility that places us at the forefront of innovation and development in the country and drives our purpose to lead the future of snacking. We are pioneers in the country in work-life balance practices such as extended maternity leave, open spaces, remote work and flexible working hours.

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.

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