Job Description

Job Description

The primary location in Purchase, NY. However, open to considering candidates for Plano, TX, Chicago, IL, and NYC.

PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics and new product development. PepsiCos Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation.

What PepsiCo Data Management and Operations does:

* Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company
* Responsible for day-to-day data collection, transportation, maintenance/curation and access to the PepsiCo corporate data asset
* Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders
* Increase awareness about available data and democratize access to it across the company
* As a member of the data engineering team, you will be a key technical expert overseeing the quality of data pipelines into and within the company, working with data architecture and data quality teams to structure high-quality data-at-rest and provisioning data for use and experimentation by various internal data customers. Youll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. With your data engineering skills, youll also work closely with the data science team to enable exploration of new data sources and the development of models to classify and bring meaning to unknown and unstructured data.

Accountabilities:

* This is a hands-on role supervising data Ingestion and Integration processes from data source systems into the enterprise data warehouse, data lake or other data storage and exploration tools (i.e., Databricks delta lake)
* Professionalize data engineering by developing standard management processes to oversee the lifecycle of ingress and egress data pipelines and customer data sandboxes under your management
* Will partner with IT, data architecture and other teams on the administration and monitoring of all data platforms to ensure data is properly transported, harmonized and made accessible across key dimensions: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations
* Performance tuning and optimization of all data ingestion and data integration processes, including data platform and databases
* Will work cross-functionally with various teams and stakeholders to resolve data issues

Qualifications/Requirements

* Bachelors Degree required
* 6+ years of work experience
* 6+ years of experience using SQL. Knowledge of a complementary scripting language (Python, R, Scala), a plus but not required
* Comfortable setting up and overseeing batch and API based data pipelines
* Experience using data tools like MFT (Managed File transfer - Tibco, IBM MQ FTE), ETL (Extract Transform and Load Informatica), Datastage, Alteryx, industrial data pipeline tools, etc.
* Experience managing pipelines into a heterogenous data architecture/technology ecosystem
* Experience with tools like Azure Data Lake (Analytics and Storage), Data Warehouse, Synapse Analytics, Amazon Redshift, Data Factory, Logic Apps
* Familiarity with Hadoop-based technologies (HDInsight, Spark, Hive, Pig, etc.) preferred

Relocation Eligible: Not Applicable
Job Type: Regular