Experteer Overview
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As Director of Data Engineering for Capital Markets, you will lead a high‑performing team to design and deliver scalable, governed data platforms powering analytics and decision‑making. You partner with Capital Markets leadership and enterprise data functions to align data architecture with business strategy and data governance standards. You’ll drive platform innovations, data integration, and ML/AI readiness to support pricing, research, and investor insights. This role offers impact by shaping data foundations that enable revenue and risk decisions in a global real estate context.
Compensaciones / Beneficios
• Define and drive Capital Markets data platform strategy, consolidating data sources into a unified, governed architecture for analytics and decision-making
• Provide technical leadership across the Data Engineering team, establishing standards and best practices
• Architect advanced data integration for structured and unstructured data to support AI/ML inputs and real-time insights at scale
• Lead the design and delivery of platform capabilities enabling intelligent search, recommendations, and automated insights through governed data services and APIs
• Design enterprise-grade data integration frameworks (APIs, event-driven patterns) for access across analytics, applications, and AI systems
• Collaborate with data science/ML teams to build production-ready data foundations, MLOps pipelines, feature stores, and governance
• Guide semantic layers, ontologies, and knowledge graphs for discoverable, reliable data for humans and AI systems
• Lead data architecture reviews, evaluations, and PoCs; promote modern data engineering practices
• Establish DataOps, observability, data quality, lineage, and compliance controls for production-ready data products
• Partner with executives, Product, and Business teams to align data platforms with Capital Markets strategy
• Hire, mentor, and grow data engineers; foster a culture of technical excellence and ownership
• Communicate roadmap and trade-offs to diverse audiences with clarity and confidence
Responsabilidades xpzdshu
• People management: 4+ years managing data engineers or similar teams
• 10+ years in data engineering/big data with enterprise-scale platforms
• 5+ years cloud experience (Azure or AWS) with services like Databricks, Azure Data Factory, Synapse, AWS Glue, EMR, Redshift
• Proficiency in Python, Java, Scala; strong PySpark/Spark expertise
• Data modeling, architecture, and scalable, cost-conscious design
• Understanding of ML lifecycle, MLOps, model governance, production ML systems
• Experience with SQL/NoSQL databases and AI-centric/vector + knowledge graphs databases
• Ability to architect and optimize complex data systems; proven technical leadership
Requisitos principales
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