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Senior Data Engineer

2 months ago

Plano, Texas, United States PepsiCo Full time
About the Role

We are seeking a highly skilled Senior Data Engineer to join our team at PepsiCo. As a key member of our data engineering team, you will be responsible for developing and overseeing our data product build & operations, driving a strong vision for how data engineering can proactively create a positive impact on the business.

Key Responsibilities
  • Develop and oversee data product build & operations, ensuring high-quality data collection, transportation, maintenance, and access.
  • Lead the development of large and complex data applications into public cloud environments, directly impacting the design, architecture, and implementation of PepsiCo's flagship data products.
  • Work closely with process owners, product owners, and business users to drive solutioning and POC discussions.
  • Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
  • 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.
  • Define and manage SLAs for data products and processes running in production.
  • Support large-scale experimentation done by data scientists.
  • Prototype new approaches and build solutions at scale.
  • Research in state-of-the-art methodologies.
  • Create documentation for learnings and knowledge transfer.
  • Create and audit reusable packages or libraries.
Requirements
  • 6+ years of overall technology experience, including at least 4+ years of hands-on software development, data engineering, and systems architecture.
  • 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
  • 4+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala, etc.
  • 3+ years in cloud data engineering experience in Azure.
  • Fluent with Azure cloud services. Azure Certification is a plus.
  • Experience with Azure Data Factory, Azure Databricks, and Azure Machine learning tools.
  • Experience with integration of multi-cloud services with on-premises technologies.
  • Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
  • Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
  • Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
  • Experience with at least one MPP database technology such as Redshift, Synapse, or SnowFlake.
  • Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
  • Experience with version control systems like Github and deployment & CI tools.
  • Experience with Statistical/ML techniques is a plus.
  • Experience with building solutions in the retail or in the supply chain space is a plus.
  • Understanding of metadata management, data lineage, and data glossaries is a plus.
  • Working knowledge of agile development, including DevOps and DataOps concepts.
  • Familiarity with business intelligence tools (such as PowerBI).
Education
  • BA/BS in Computer Science, Math, Physics, or other technical fields.
Skills, Abilities, Knowledge
  • Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior-level management.
  • Proven track record of leading, mentoring data teams.
  • Strong change manager. Comfortable with change, especially that which arises through company growth.
  • Ability to understand and translate business requirements into data and technical requirements.
  • High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
  • Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
  • Strong leadership, organizational, and interpersonal skills; comfortable managing trade-offs.
  • Foster a team culture of accountability, communication, and self-management.
  • Proactively drives impact and engagement while bringing others along.
  • Consistently attain/exceed individual and team goals.
  • Ability to lead others without direct authority in a matrixed environment.
Competencies
  • Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
  • Understands both the engineering and business side of the Data Products released.
  • Places the user in the center of decision making.
  • Teams up and collaborates for speed, agility, and innovation.
  • Experience with and embraces agile methodologies.
  • Strong negotiation and decision-making skill.
  • Experience managing and working with globally distributed teams.