Group Lead IT - Data Engineering Chapter

Job Description

Group Lead, Data Engineering

Position Summary

The Kraft Heinz Information Technology organization is hiring a Group Lead for Data Engineering who will work closely with cross-functional teams to build high quality data/analytic products. These solutions will generate insights from the organization’s connected data to advance data-driven decision-making across the enterprise. The individual for this position will be an anchor technical leader providing expertise in the areas of data engineering, data architecture, data management, data quality, and data governance. They will manage internal stakeholders, facilitate the development and training of data engineers within projects, as well as provide hands-on design and development of platform capabilities.

Primary Responsibilities

• Manage strategy and allocation of data engineering resources for cross-functional delivery teams within the region
• Hiring governance for external and internal data engineer resources globally
• Lead the design and development of technical training programs for data engineers
• Establish and enforce best practices and controls for data engineering at scale
• Conduct thorough code reviews to ensure solution consistency and accuracy across all teams
• Architect and build robust frameworks for data ingestion, processing, integration, and governance
• Manage a pipeline of platform and framework improvements to enhance the cloud analytics platform’s efficiency and security
• Develop and evaluate new technologies and tools for data engineering teams
• Collaborate with software vendors to align their products with KHC’s needs and drive innovation
• Work closely with product owners, stakeholders, and executives to identify and mitigate potential data challenges.
  
  
  

• Bachelor’s degree in Computer Science, Statistics, Business, Information Technology, or a related field (Master degree preferred)
• 6+ years of experience in data engineering or architecture roles
• Expert in software development, including design patterns and framework development
• Expert in core Python programming language (not limited to PySpark or analytical libraries)
• Expert SQL development and deep analytical skills
• Expert with automated code testing (pytest / unittest) and data testing (great expectations / dbt / etc)
• Proven experience with data warehousing solutions (e.g., Snowflake, BigQuery)
• Solid experience with major cloud computing services and infrastructure (Azure preferred)
• Expert knowledge of database technologies (relational, NoSQL, BigData, cloud databases)
• Familiarity with BI tools (Tableau, Power BI, Alteryx, Looker)
• Familiarity with the Linux operating system
• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
  
  
  

• 5+ years of experience building enterprise-level data solutions
• Proven ability to design and build data frameworks and platforms on major cloud providers
• Demonstrated experience creating data assets for mission-critical applications
• Proven experience applying DevOps (Build + Run + Support) practices in the data domain
• Experience with Agile methodologies
  
  
  

• Experience leading and managing cross-functional teams
• Expertise in applying cloud technologies within a DataOps and DevOps framework
  
  
  

• Excellent communication skills, with the ability to explain complex technical concepts clearly and concisely
• Strong problem-solving skills with the ability to analyze complex information and present it effectively
• Proven ability to collaborate effectively with teams to create innovative solutions.
  
  
  

• Passionate about technology and excited about the impact of emerging / disruptive technologies
• Proven learning agility on both the technical and business process realms
• Wants to unleash inner self-starter and work in an environment that fosters entrepreneurial minds
• Believes in culture of brutal transparency and trust and open to learning new ideas outside scope or knowledge