Lead Engineer- Data Platform
NewBe an early applicantSummary
Lead Engineer for Deutsche Bank's data platform in Madrid: a hands-on technical leadership role designing and evolving a hybrid cloud/on-prem data platform, setting standards, and mentoring a small team. Core stack is Snowflake, Apache Airflow, and Kafka, with Python/SQL, Terraform, and CI/CD in a regulated banking environment.
Experteer Overview
Por favor, presente su candidatura sin demora si su perfil encaja bien con este puesto, debido al alto nivel de interés.
In this role you will lead the design and evolution of a hybrid data platform, shaping scalable data solutions for the enterprise. You’ll steer a small, high-impact team, setting technical direction and contributing to architecture and code. You’ll ensure reliability, security, and cost-efficient operations while partnering with architecture, security, and governance teams. This is a hands-on leadership role that blends engineering excellence with strategic impact in a regulated environment.
Compensaciones / Beneficios
• Own end-to-end architecture and evolution of the data platform across hybrid cloud and on-prem environments
• Define technical roadmap, standards, and reusable patterns for orchestration, scheduling, and data processing
• Lead architectural decisions, proofs of concept, and adoption plans focused on scalability, interoperability, security, operability, and TCO
• Establish reliability, observability, and operational standards for data platform components (monitoring, alerting, recovery, capacity, SLOs)
• Drive platform automation via infrastructure as code, CI/CD, automated testing, and self-service capabilities
• Collaborate with architecture, security, governance, and application teams to meet enterprise standards and regulatory requirements
• Stay hands-on in architecture and code, lead design and code reviews, mentor engineers, and promote engineering excellence
Responsabilidades
• 12+ years in data or platform engineering with enterprise-scale data platforms
• Deep Snowflake expertise (architecture, ingestion, transformation, workload management, cost optimization, governance)
• Strong Airflow production experience (DAG patterns, dependency management, testing, monitoring, failure recovery)
• Strong Apache Kafka experience and event-driven architectures (design, Connect, replay strategies)
• Proven ability to integrate batch xqbhyrx and streaming pipelines across Snowflake, Airflow, and Kafka
• Advanced Python and SQL; Java is beneficial for Kafka-based services
• Experience with Terraform, Git, CI/CD; OpenShift or Kubernetes is desirable
• Understanding of reliability, observability, data quality, security and compliance in regulated environments
• Technical leadership experience (direction, reviews, mentoring, stakeholder communication)
• English fluency; experience leveraging AI tools responsibly to improve productivity
Requisitos principales
• hybrid working model
• healthcare options
• retirement plan
• perks
• inclusive culture
Por favor, presente su candidatura sin demora si su perfil encaja bien con este puesto, debido al alto nivel de interés.
In this role you will lead the design and evolution of a hybrid data platform, shaping scalable data solutions for the enterprise. You’ll steer a small, high-impact team, setting technical direction and contributing to architecture and code. You’ll ensure reliability, security, and cost-efficient operations while partnering with architecture, security, and governance teams. This is a hands-on leadership role that blends engineering excellence with strategic impact in a regulated environment.
Compensaciones / Beneficios
• Own end-to-end architecture and evolution of the data platform across hybrid cloud and on-prem environments
• Define technical roadmap, standards, and reusable patterns for orchestration, scheduling, and data processing
• Lead architectural decisions, proofs of concept, and adoption plans focused on scalability, interoperability, security, operability, and TCO
• Establish reliability, observability, and operational standards for data platform components (monitoring, alerting, recovery, capacity, SLOs)
• Drive platform automation via infrastructure as code, CI/CD, automated testing, and self-service capabilities
• Collaborate with architecture, security, governance, and application teams to meet enterprise standards and regulatory requirements
• Stay hands-on in architecture and code, lead design and code reviews, mentor engineers, and promote engineering excellence
Responsabilidades
• 12+ years in data or platform engineering with enterprise-scale data platforms
• Deep Snowflake expertise (architecture, ingestion, transformation, workload management, cost optimization, governance)
• Strong Airflow production experience (DAG patterns, dependency management, testing, monitoring, failure recovery)
• Strong Apache Kafka experience and event-driven architectures (design, Connect, replay strategies)
• Proven ability to integrate batch xqbhyrx and streaming pipelines across Snowflake, Airflow, and Kafka
• Advanced Python and SQL; Java is beneficial for Kafka-based services
• Experience with Terraform, Git, CI/CD; OpenShift or Kubernetes is desirable
• Understanding of reliability, observability, data quality, security and compliance in regulated environments
• Technical leadership experience (direction, reviews, mentoring, stakeholder communication)
• English fluency; experience leveraging AI tools responsibly to improve productivity
Requisitos principales
• hybrid working model
• healthcare options
• retirement plan
• perks
• inclusive culture