.overviewwe are pepsicojoin pepsico and dare for better!
we are the perfect place for curious people, thinkers, and change agents.
from leadership to front lines, we're excited about the future and working together to make the world a better place.being part of pepsico means being part of one of the largest food and beverage companies in the world, with our iconic brands consumed more than a billion times a day in more than 200 countries.our product portfolio, which includes 22 of the world's most iconic brands, such as sabritas, gamesa, quaker, pepsi, gatorade, and sonrics, has been a part of mexican homes for more than 116 years.a career at pepsico means working in a culture where all people are welcome.
here, you can dare to be you.
no matter who you are, where you're from, or who you love, you can always influence the people around you and make a positive impact in the world.know more: pepsicojobsjoin pepsico, dare for better.responsibilitiesthe opportunitya lead platform engineer to be a key player in our transformation and modernization programs, leading the migration of applications from legacy systems to azure-based architectures.
this role involves designing, implementing, and optimizing scalable, cloud-native data solutions using databricks, azure devops (ado), and agile development methodologies.
as an active contributor to code development, you will help drive automation, operational excellence, and data quality across our platforms.
you will collaborate with stakeholders and product teams to create solutions that enable our data-driven decision-making capabilities.your impactas lead data platform engineer – transformation & modernization your scope would consist of:lead the migration and modernization of data platforms, moving applications and pipelines to azure-based solutions.actively contribute to code development in projects and services.manage and scale data pipelines from internal and external data sources to support new product launches and ensure high data quality.develop automation and monitoring frameworks to capture key metrics and operational kpis for pipeline performance.implement best practices around systems integration, security, performance, and data management.collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (poc) discussions.develop and optimize procedures to transition data into production.define and manage slas for data products and operational processes.prototype and build scalable solutions for data engineering and analytics.research and apply state-of-the-art methodologies in data and platform engineering.create and maintain technical documentation for knowledge sharing.develop reusable packages and libraries to enhance development efficiency