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# Lead Engineer & Data Platform

- **Company:** Q Tech
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Automation of Tests, Continuous Integration, Data Infrastructure, Identity and Access Management, Python (Programming Language), OpenShift, SQL Databases, Enterprise Data Management, Data Processing, Snowflake, Git, Event Driven Architecture, Kubernetes, Infrastructure Automation Frameworks, Apache Kafka, Data Management, Terraform
- **Published:** August 27, 2026
- **Apply:** https://es.indeed.com/viewjob?jk=e74fe24fa5e345e3

## About the Role

* 12+ years of experience in data/platform engineering, designing and operating enterprise-scale data platforms.
 * Deep, hands-on Snowflake expertise (architecture, ingestion, transformation, workload management, cost, governance).
 * Production experience with Apache Airflow and Apache Kafka / event-driven architectures.
 * Proven ability to integrate batch and streaming pipelines (Snowflake, Airflow, Kafka).
 * Advanced Python and SQL; Java experience for Kafka-based services/connectors is a plus.
 * Terraform, Git, CI/CD; OpenShift or Kubernetes experience is a plus.
 * Experience in regulated environments: security, data quality, access management and compliance.
 * Proven technical leadership: team direction, mentoring and communication with technical and business stakeholders.
 * Fluent English, written and spoken.

If you're passionate about building robust data platforms, leading with strong technical judgment, and making an impact in a global financial environment, we'd love to talk to you.

## Description

* Owning the end-to-end architecture and evolution of the enterprise data platform across hybrid environments.
 * Setting the technical direction: roadmap, standards and reusable patterns for orchestration, scheduling and data processing.
 * Leading architectural decisions, proofs of concept and adoption plans focused on scalability, security and cost.
 * Establishing reliability, observability and operational standards (monitoring, alerting, failure recovery, SLOs).
 * Driving automation through infrastructure as code, CI/CD and automated testing.
 * Staying hands-on: design and code reviews, mentoring, and championing a culture of engineering excellence.


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