Sr Data Engineer Jobs

Overview

• 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
• Increase awareness about available data and democratize access to it across the company
• Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders

As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems.

Responsibilities

• Define and manage SLA’s for data products and processes running in production.
• Create and audit reusable packages or libraries.
• Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
• Responsible for implementing best practices around systems integration, security, performance and data management.
• Support large-scale experimentation done by data scientists.
• Prototype new approaches and build solutions at scale.
• Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners.
• Develop and optimize procedures to “productionalize” data science models.
• Active contributor to code development in projects and services.
• Create documentation for learnings and knowledge transfer.
• Research in state-of-the-art methodologies.
• Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products.
• Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.
• Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.

Qualifications

• Experience with at least one MPP database technology such as Redshift, Synapse or SnowFlake.
• Experience with integration of multi cloud services with on-premises technologies.
• Familiarity with business intelligence tools (such as PowerBI).
• Fluent with Azure cloud services. Azure Certification is a plus.
• BA/BS in Computer Science, Math, Physics, or other technical fields.
• 4+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
• 2+ years in cloud data engineering experience in Azure.
• 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools.
• Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
• Experience with Statistical/ML techniques is a plus.
• Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
• Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
• Experience with building solutions in the retail or in the supply chain space is a plus
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Experience with version control systems like Github and deployment & CI tools.
• Understanding of metadata management, data lineage, and data glossaries is a plus.
• 6+ years of overall technology experience that includes at least 4+ years of hands-on software development, data engineering, and systems architecture.
• Working knowledge of agile development, including DevOps and DataOps concepts.

• Proven track record of leading, mentoring data teams.
• Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs.
• Consistently attain/exceed individual and team goals
• Proactively drives impact and engagement while bringing others along.
• Ability to understand and translate business requirements into data and technical requirements.
• Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management.
• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Strong change manager. Comfortable with change, especially that which arises through company growth.
• High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
• Ability to lead others without direct authority in a matrixed environment.
• Foster a team culture of accountability, communication, and self-management.

Competencies

• Experience managing and working with globally distributed teams.
• Experience with and embraces agile methodologies.
• Places the user in the center of decision making.
• Strong negotiation and decision-making skill.
• Understands both the engineering and business side of the Data Products released.
• Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
• Teams up and collaborates for speed, agility, and innovation.

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