Director, Data Engineering

About the role

The Director, Data Engineering will lead enterprise data platform strategy and execution within the Corporate Data Office. This role provides strategic and hands-on technical leadership for the design, implementation, and optimization of modern, cloud-native data platforms.

Responsibilities

• Help others build code to extract raw data
• Coach the team on techniques to validate its quality
• Apply deep data knowledge to ensure the correct data is ingested across the pipeline
• Guide the development of data tools used to transform, manage, and access data
• Advise the team on writing and validating code to test the storage and availability of data platforms
• Oversee the implementation of performance monitoring protocols across data pipelines
• Coach the team on building visualizations and aggregations to monitor pipeline health
• Coach others on implementing solutions and self-healing processes that minimize points of failure across multiple product features
• Help others identify data governance needs
• Oversee data accessibility within your assigned pipelines
• Prepare team members for meetings with appropriate stakeholders across teams and address concerns around data requirements by providing guidance on feature estimation
• Help others assess data costs, access, usage, use cases, dependencies across products, and availability for business or customer scenarios related to one or more product features

Requirements

• Minimum Bachelor’s degree in computer science, information systems, data engineering, or related field (or equivalent experience)
• 12+ years of progressive experience in data engineering, data architecture, or enterprise data platforms
• 5+ years of leadership experience managing managers and technical teams in cross-functional enterprise environments
• Deep hands-on experience with AWS cloud architecture and services supporting large-scale data ecosystems
• Advanced hands-on experience with Snowflake, including architecture design, modeling, performance optimization, and security configuration
• Proven experience implementing and managing Qlik Replicate, Qlik Compose, or similar CDC/data integration platforms
• Demonstrated success delivering enterprise-scale data modernization initiatives
• Extensive experience with SQL and relational databases
• Experience building and optimizing end-to-end data pipelines supporting data lake, data warehouse, operational analytics, and AI/ML workloads
• Experience implementing CI/CD frameworks using GitHub, GitLab, Azure DevOps, or similar platforms

Preferred

• 6+ years of hands-on dimensional, and analytic modeling experience in Conceptual, Logical and Physical Data Models
• Knowledge of metadata management, data modeling, and related tools (Qlik Compose, Erwin or ER Studio or others) including Source-to-Target mapping working directly with the developers, data architect and engineers
• Design data models to ensure future business flexibility, ease of use and sustainable architecture
• Consider ELT/ETL and Reporting challenges in designing data models
• Hands-on experience in data requirements and technical requirements gathering
• Create cross-functional documentation for multiple stakeholders and teams
• Experience in the Risk & Compliance domain
• Google Cloud, Amazon Web Services, or Azure
• CICD in GitHub, GitLab, or Azure DevOps
• Terraform or other Infrastructure as Code technology
• Qlik Replicate, Qlik Compose
• PowerBI
• Experience with Infrastructure-as-Code technologies (Terraform or equivalent)