Overview

We are seeking a visionary and highly experienced Director of Data Integration Platforms to spearhead the development and implementation of our data integration strategy. This pivotal role entails building and scaling a cutting-edge data integration platform that drives innovation and empowers the organization with actionable insights.

The ideal candidate will combine technical expertise with leadership excellence, showcasing a proven history of success in designing, developing, and managing large-scale data integration platforms. They should possess the ability to foster and guide a high-performing team, inspiring innovation and collaboration.

Responsibilities

• Develop and execute a strategic roadmap for data integration platforms, ensuring alignment with business goals. Focus areas include data warehousing, data lakes, data pipelines, data quality, and governance.
• Team Leadership: Recruit, mentor, and lead a team of data engineers, architects, and analysts. Cultivate a culture of collaboration, innovation, and excellence.
• Platform Architecture & Engineering: Direct the design, development, and deployment of data integration infrastructure leveraging cloud platforms (AWS, Azure, GCP), data warehousing technologies (e.g., Snowflake, Redshift), and data lake solutions (e.g., Databricks, AWS S3).
• Data Quality & Governance: Establish robust standards and governance practices to ensure data accuracy, security, and consistency across the organization.
• Stakeholder Collaboration: Partner with business leaders to identify data needs and transform them into practical, actionable solutions that support organizational objectives.
• Champion Data-Driven Decisions: Advocate for leveraging insights across the organization to empower teams and drive informed decision-making processes.
• Stay Ahead of Trends: Continuously monitor and assess emerging technologies and industry best practices to ensure the organization remains at the forefront of data integration and analytics innovation.

• The expected compensation range for this position is between $125,900 - $249,900.
• Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
• Bonus based on performance and eligibility target payout is 25% of annual salary paid out annually and an additional target payout of 10% of annual salary is paid out over 3 years following the end of the performance period.
• Long term incentive equity may be awarded based on eligibility and performance.
• Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
• In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.

• Leadership Experience: Over 15 years of experience in data integration management and analytics, including a minimum of 5 years leading high-performing data teams.
• Technical Expertise: In-depth knowledge of data warehousing, ETL, data lakes, data pipelines, data integration, and data quality principles. Proficiency with cloud-based platforms such as AWS, Azure, and GCP is required.
• Hands-On Experience: Skilled in using data engineering tools and technologies, including SQL, Python, Spark, and ETL tools like Informatica, as well as data visualization tools such as Tableau and Power BI.
• Communication Skills: Exceptional communication, presentation, and interpersonal abilities to effectively convey complex technical concepts to both technical and non-technical audiences.
• Strategic Planning: Proven ability to develop and implement long-term data strategies aligned with business goals.
• Data Governance Expertise: Experience in implementing data governance frameworks, adhering to data security best practices, and ensuring compliance with regulations.
• Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field is required. Advanced degrees (Master's or PhD) are preferred.

• Experience in machine learning and artificial intelligence.
• Familiarity with data science platforms and tools.
• Proficiency with Agile methodologies.