[Remote] Director of Data Engineering & Platforms

Note: The job is a remote job and is open to candidates in USA. Cotality is a leading company in property intelligence, dedicated to making the property industry faster and smarter. They are seeking a Director of Data Engineering & Platforms to lead data transformation initiatives and establish robust data architecture frameworks, driving technical leadership and strategic direction for their data platform.

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, with explicit milestones for AI readiness
• 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 optimized for both BI and AI workloads
• Direct the development of robust ETL/ELT processes using Matillion, Python-based pipeline frameworks, 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
• Partner with AI/ML and product engineering teams to ensure the data layer supports LLM-powered applications reliably and at scale
• Provide architectural direction for retrieval and grounding pipelines, including vector stores, embedding workflows, and hybrid search infrastructure
• Define standards for data preparation for AI, covering metadata enrichment, context optimization, and semantic indexing
• Build observability into AI data flows and monitor for drift and retrieval quality degradation
• Guide the team's evaluation and adoption of emerging AI-native data tools, including vector databases and LLM orchestration frameworks
• Establish governance frameworks for AI data use, including data lineage into models, PII controls upstream of LLM consumption, and output auditability
• Define the organization's standards for acceptable AI data quality thresholds and remediation workflows
• Partner with Security and Compliance to ensure AI data pipelines meet regulatory and privacy requirements
• Build, mentor, and lead a high-performing data engineering team with strong core data engineering fundamentals and a growing fluency in modern AI infrastructure
• 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 where AI is a tool the team uses daily, not a project they hand off
• Develop talent through coaching, training, and career development opportunities, with an emphasis on AI-era skills including Python, vector search, and agentic pipeline concepts
• 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, with particular attention to AI/ML tooling and agentic workflow frameworks
• Lead proof-of-concepts and pilots for innovative data solutions, including AI-powered pipeline automation and LLM-grounded analytics
• 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

Skills

• 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
• Demonstrated interest in AI/ML data infrastructure, whether through independent projects, coursework, or applied experimentation
• Ability to engage credibly with engineers building LLM-powered systems and make sound architectural decisions without being the implementer
• Bachelor's or master's degree in computer science, Information Systems, or a related field
• Proficiency in Python and experience with Spark or other data processing frameworks
• Knowledge of CI/CD practices and DevOps for data pipelines
• Has independently explored or prototyped with vector databases, RAG pipelines, or LLM grounding concepts
• Familiarity with LLM orchestration frameworks such as LangChain or LlamaIndex
• Exposure to agentic workflow concepts and the data contracts they require
• Experience with real-time data integration and streaming architecture
• Background in implementing data security and privacy controls
• Understanding of API design and microservices architectures
• Experience in insurance, financial services, or real estate industries

Benefits

• Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.
• Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.
• Health: Multiple medical plan options with mental health and wellness support offerings.
• Retirement: 401(k) with company match and vesting after one year.
• Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.
• Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!

Company Overview