[Remote] Director of Data Engineering & Platforms

Note: The job is a remote job and is open to candidates in USA. Cotality is committed to transforming the property industry through innovative data solutions and is seeking a Director of Data Engineering & Platforms to lead their data transformation initiatives. This role involves designing and maintaining the enterprise data ecosystem, ensuring alignment with business objectives, and driving technical leadership in data engineering and AI enablement.ResponsibilitiesLead the development and implementation of our data engineering strategy, architecture roadmap, and technical standardsOversee the design and evolution of our data ecosystem utilizing Data Vault methodologies and Data Mesh principlesEstablish governance and quality frameworks across Bronze (raw), Silver (transformed), and Gold (consumption-ready) data layersPartner with Product Management to align data platform capabilities with business objectives and market demandsDrive the technical roadmap for data integration, transformation, and delivery systems, with explicit milestones for AI readinessProvide technical leadership and oversight for the data engineering team, ensuring best practices in data pipelines, transformations, and deliveryOversee the design and implementation of Snowflake data architecture including warehousing, marts, and access patterns optimized for both BI and AI workloadsDirect the development of robust ETL/ELT processes using Matillion, Python-based pipeline frameworks, and other modern data integration toolsGuide the implementation of data quality monitoring, lineage tracking, and metadata managementEstablish standards for data modeling, transformation logic, and performance optimizationPartner with AI/ML and product engineering teams to ensure the data layer supports LLM-powered applications reliably and at scaleProvide architectural direction for retrieval and grounding pipelines, including vector stores, embedding workflows, and hybrid search infrastructureDefine standards for data preparation for AI, covering metadata enrichment, context optimization, and semantic indexingBuild observability into AI data flows and monitor for drift and retrieval quality degradationGuide the team's evaluation and adoption of emerging AI-native data tools, including vector databases and LLM orchestration frameworksEstablish governance frameworks for AI data use, including data lineage into models, PII controls upstream of LLM consumption, and output auditabilityDefine the organization's standards for acceptable AI data quality thresholds and remediation workflowsPartner with Security and Compliance to ensure AI data pipelines meet regulatory and privacy requirementsBuild, mentor, and lead a high-performing data engineering team with strong core data engineering fundamentals and a growing fluency in modern AI infrastructureCollaborate cross-functionally with Product Management, Data Analytics, Data Systems, Cloud Engineering, and product teamsFoster a culture of innovation, continuous improvement, and technical excellence where AI is a tool the team uses daily, not a project they hand offDevelop talent through coaching, training, and career development opportunities, with an emphasis on AI-era skills including Python, vector search, and agentic pipeline conceptsPromote adaptive methodologies and DevOps practices within the data engineering disciplineOversee the technical implementation of Power BI reporting solutions and analytics platformsEnsure data pipelines efficiently support BI reporting needs and business intelligence requirementsPartner with Data Analytics teams to optimize data structures for analytical workloadsGuide the design of data models that enable self-service analytics and reportingEstablish patterns for efficient and secure data access across the organizationEvaluate emerging technologies and methodologies for potential integration into our data platform, with particular attention to AI/ML tooling and agentic workflow frameworksLead proof-of-concepts and pilots for innovative data solutions, including AI-powered pipeline automation and LLM-grounded analyticsDevelop the technical foundation to support advanced analytics and machine learning initiativesGuide the evolution of our data architecture to support real-time and streaming use casesStay current with industry trends and incorporate best practices into our data ecosystemSkillsBachelor's degree from an accredited institution or equivalent professional experience with demonstrated capability8+ years of progressive experience in data engineering, data architecture, or related technical roles5+ years of leadership experience managing data engineering teams and initiativesExtensive experience with modern data platforms, particularly Snowflake and cloud-based data solutionsDeep understanding of data modeling techniques including Data Vault, dimensional modeling, and Data Mesh conceptsHands-on experience with ETL/ELT tools like Matillion and data integration patternsStrong knowledge of SQL Server, Cosmos DB, and database technologiesExperience with Power BI or similar BI platforms and understanding of reporting architecturesProven track record implementing data governance, quality, and metadata management solutionsExperience partnering with product teams and translating business requirements into technical solutionsDemonstrated interest in AI/ML data infrastructure, whether through independent projects, coursework, or applied experimentationAbility to engage credibly with engineers building LLM-powered systems and make sound architectural decisions without being the implementerBachelor's or master's degree in computer science, Information Systems, or a related fieldProficiency in Python and experience with Spark or other data processing frameworksKnowledge of CI/CD practices and DevOps for data pipelinesHas independently explored or prototyped with vector databases, RAG pipelines, or LLM grounding conceptsFamiliarity with LLM orchestration frameworks such as LangChain or LlamaIndexExposure to agentic workflow concepts and the data contracts they requireExperience with real-time data integration and streaming architectureBackground in implementing data security and privacy controlsUnderstanding of API design and microservices architecturesExperience in insurance, financial services, or real estate industriesBenefitsTime 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 OverviewCotality offers data-driven insights and analytics for real estate professionals to support informed decision-making. It was founded in 2010, and is headquartered in Austin, Texas, USA, with a workforce of 1001-5000 employees. Its website is https://www.cotality.com.