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Director, Data Engineering (Capital Markets)

Madrid, ESP💼 Full-time🗓 2026-06-02 → 2026-07-30

Core

Lead the Capital Markets data engineering function to define strategy, architecture, and operations for data platforms powering analytics, pricing, research, and investor-facing insights in the real estate and investment management sector.

Role type

Director, Data Engineering (Capital Markets)

Builds

Unified, governed, and scalable data platforms and pipelines for Capital Markets analytics and decision-making.

Domain

Real Estate & Investment Management / Capital Markets / Data Engineering

Deliverable

production ML models | product features | dashboards & analysis | infrastructure

Required skills

People management (4+ years), Data Engineering & Big Data architecture (10+ years), Cloud platforms (Azure/AWS), Server-side programming (Python, Java, Scala), PySpark/Spark, Data modeling & architecture, MLOps & ML lifecycle, Diverse data technologies (SQL, NoSQL, Vector/Graph DBs), Technical leadership & mentoring.

Preferred skills

Semantic layers & knowledge graphs, Streaming architectures (Kafka, Flink), DevOps & IaC (Terraform, Kubernetes), LLM workflows & RAG, AI-augmented development, Data governance & compliance.

Technologies

Azure, AWS, Databricks, Azure Data Factory, Synapse, AWS Glue, EMR, Redshift, Python, Java, Scala, PySpark, Spark, SQL, PostgreSQL, Cosmos DB, MongoDB, Cassandra, Pinecone, Weaviate, Neo4j, Amazon Neptune, Kafka, Spark Streaming, Flink, Terraform, CloudFormation, Kubernetes, EKS, AKS, LangChain, LlamaIndex, CrewAI, AutoGen.

Responsibilities

Define Capital Markets data platform strategy and architecture; Provide technical leadership and set architectural standards; Architect data integration strategies for structured/unstructured data; Lead design of platform capabilities for intelligent search and automated insights; Design enterprise-grade data integration frameworks and API strategies; Partner with data science to architect production-ready data foundations and MLOps pipelines; Guide design of semantic layers and knowledge graphs; Lead data architecture reviews and technology evaluations; Establish DataOps practices, observability, and data governance; Partner with executive leadership to align data capabilities with business strategy; Hire, mentor, and grow data engineers; Serve as the data engineering voice in cross-functional forums.

Seniority

Director, strategic leadership with hands-on technical credibility

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