D&A Supply Chain Planning Data Engineer

Looking for a savvy Data Engineer to join team of Modeling / Architect experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.This role requires a flexible working schedule, including potential weekend support for critical operations, while maintaining a 40-hour work week.

In this role, you will assist in maintaining the MDLZ DataHub Google BigQuery data pipelines and corresponding platforms (on-prem and cloud), working closely with global teams on DataOps initiatives. The D4GV platform spans across three key GCP instances: NALA, MEU, and AMEA, supporting the global rollout of o9 across all Mondelēz BUs over the next three years

• 5+ years of overall industry experience and minimum of 2-4 years of experience building and deploying large scale data processing pipelines in a production environment
• Focus on excellence: Has practical experience of Data-Driven Approaches, Is familiar with the application of Data Security strategy, Is familiar with well know data engineering tools and platforms
• Technical depth and breadth : Able to build and operate Data Pipelines, Build and operate Data Storage, Has worked on big data architecture within Distributed Systems. Is familiar with Infrastructure definition and automation in this context. Is aware of adjacent technologies to the ones they have worked on. Can speak to the alternative tech choices to that made on their projects.
• Implementation and automation of Internal data extraction from SAP BW / HANA
• Implementation and automation of External data extraction from openly available internet data sources via APIs
• Data cleaning, curation and enrichment by using Alteryx, SQL, Python, R, PySpark, SparkR
• Data ingestion and management in Hadoop / Hive
• Preparing consolidated DataMart for use by Data Scientists and managing SQL Databases
• Exposing data via Alteryx, SQL Database for consumption in Tableau
• Data documentation maintenance/update
• Collaboration and workflow using a version control system (e.g., Git Hub)
• Learning ability : Is self-reflective, Has a hunger to improve, Has a keen interest to drive their own learning. Applies theoretical knowledge to practice
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Flexible Working Hours: This role requires the flexibility to work non-traditional hours, including providing support during off-hours or weekends for critical data pipeline job runs, deployments, or incident response, while ensuring the total work commitment remains a 40-hour week.

•Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.