Director of Data Engineering & Platforms

Cotality is a leader in property intelligence, committed to innovation and inclusivity. They are seeking a remote Director of Data Engineering & Platforms to lead data transformation initiatives and establish robust data architecture frameworks, partnering with various teams to convert raw data into actionable business intelligence.

Responsibilities:

• Lead the development and implementation of our data engineering strategy, architecture roadmap, and technical standards
• Oversee the design and evolution of our data ecosystem utilizing Data Vault methodologies and Data Mesh principles
• Establish governance and quality frameworks across Bronze (raw), Silver (transformed), and Gold (consumption-ready) data layers
• Partner with Product Management to align data platform capabilities with business objectives and market demands
• Drive the technical roadmap for data integration, transformation, and delivery systems
• Provide technical leadership and oversight for the data engineering team, ensuring best practices in data pipelines, transformations, and delivery
• Oversee the design and implementation of Snowflake data architecture including warehousing, marts, and access patterns
• Direct the development of robust ETL/ELT processes using Matillion and other modern data integration tools
• Guide the implementation of data quality monitoring, lineage tracking, and metadata management
• Establish standards for data modeling, transformation logic, and performance optimization
• Build, mentor, and lead a high-performing
• Collaborate cross-functionally with Product Management, Data Analytics, Data Systems, Cloud Engineering, and product teams
• Foster a culture of innovation, continuous improvement, and technical excellence
• Develop talent through coaching, training, and career development opportunities
• Promote adaptive methodologies and DevOps practices within the data engineering discipline
• Oversee the technical implementation of Power BI reporting solutions and analytics platforms
• Ensure data pipelines efficiently support BI reporting needs and business intelligence requirements
• Partner with Data Analytics teams to optimize data structures for analytical workloads
• Guide the design of data models that enable self-service analytics and reporting
• Establish patterns for efficient and secure data access across the organization
• Evaluate emerging technologies and methodologies for potential integration into our data platform
• Lead proof-of-concepts and pilots for innovative data solutions, including AI/ML enablement
• Develop the technical foundation to support advanced analytics and machine learning initiatives
• Guide the evolution of our data architecture to support real-time and streaming use cases
• Stay current with industry trends and incorporate best practices into our data ecosystem

Requirements:

• Bachelor's degree from an accredited institution or equivalent professional experience with demonstrated capability
• 8+ years of progressive experience in data engineering, data architecture, or related technical roles
• 5+ years of leadership experience managing data engineering teams and initiatives
• Extensive experience with modern data platforms, particularly Snowflake and cloud-based data solutions
• Deep understanding of data modeling techniques including Data Vault, dimensional modeling, and data mesh concepts
• Hands-on experience with ETL/ELT tools like Matillion and data integration patterns
• Strong knowledge of SQL Server, Cosmos DB, and database technologies
• Experience with Power BI or similar BI platforms and understanding of reporting architectures
• Proven track record implementing data governance, quality, and metadata management solutions
• Experience partnering with product teams and translating business requirements into technical solutions
• Bachelor's or Master's degree in Computer Science, Information Systems, or a related field
• Experience with Python, Spark, or other data processing frameworks
• Knowledge of CI/CD practices and DevOps for data pipelines
• Familiarity with AI/ML tooling and data preparation for machine learning
• Experience with real-time data integration and streaming architectures
• Background in implementing data security and privacy controls
• Understanding of API design and microservices architectures
• Experience in the insurance, financial services, or real estate industries