Data Engineering Manager
hace 13 horas
Overview:
**Are you ready to drive PepsiCo’s digital evolution and accelerate transformation across our global operations?**
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 PepsiCo’s global business scale to enable business insights, advanced analytics and new product development. PepsiCo’s **Enterprise Data Foundation** **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** **Enterprise Data Foundation team **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-functional 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.
**Responsibilities**:
**Your day to day with us**
- Provide leadership and management to a team of data engineers, managing processes and their flow of work, vetting their designs, and mentoring them to realize their full potential.
- Oversee work with internal clients and external partners to structure and store data into unified taxonomies and link them together with standard identifiers.
- 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.
- Responsible for implementing best practices around systems integration, security, performance and data management.
- Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
- 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 SLA’s 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.
Qualifications:
**What you will need to succeed**
- 8+ years of overall technology experience that includes at least 6+ years of hands-on software development, data engineering, and systems architecture.
- 6+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
- 6+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
- 4+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).
- Fluent with Azure cloud services. Azure Certification is a plus.
- Experience scaling and managing a team of engineers.
- Experience with integration of multi cloud services with on-premises technologies.
- Experience with at least one MPP database technology such as Databricks, Synapse or SnowFlake.
- Experience with version control systems like Github and deployment & CI tools.
**Additional qualifications that will make you stand out for this position**
- 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.
**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, hiring and scaling data teams.
- Strong change manager. Comfortable with change, especially that which arises through company growth. Able to lead a team effectively through times of change.
- Ability to understand and translate business requirements into data and technical req
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