Manel Dueñas
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Manel Dueñas Triguero

Head of Data / Lead Principal Data Engineer

I build and evolve cloud-native data platforms end-to-end — combining architectural ownership, governance, and hands-on engineering in AWS lakehouse and streaming environments.

Lleida, Spain
Download CV

Two CV versions: leadership-focused and technical depth.

End-to-end ownershipPlatform scopeIngestion → modeling → consumption
Reliability & governanceCore focusQuality, metadata, observability
Batch + real-timeWorkloadsStreaming and scheduled pipelines
Hands-on leadershipApproachArchitecture + delivery

What I do

Senior data leadership with strong engineering depth — designed for regulated, high-scale environments.

  • Own data platform strategy and evolution, transforming legacy systems into modern cloud-native platforms.
  • Design architectures that support both batch and real-time analytics at scale.
  • Treat governance, data quality, and metadata as first-class platform capabilities.
  • Enable trusted analytics through well-defined data models and reliable datasets.
  • Drive observability, reliability, and operational excellence across data workflows.
  • Introduce infrastructure as code and CI/CD practices to improve stability and scalability.

Areas of expertise

A balanced profile across engineering, platform architecture, and data leadership.

Data engineering

Batch and streaming pipelines, pragmatic modeling, and reliable delivery end-to-end.

Cloud & platform (AWS)

Cloud-native lakehouse and event-driven orchestration with strong automation practices.

Governance & quality

Trust through quality checks, metadata, lineage mindset, and platform observability.

Leadership

Hands-on technical leadership: architectural ownership, mentoring, and execution.

Experience

Highlights from my current professional role.

Fintonic

Fintech · regulated environment

Head of Data / Lead Data Engineer

Owned the design and evolution of a cloud-native AWS lakehouse platform, combining architectural leadership with hands-on engineering across batch and real-time workloads.

  • Led the design and delivery of a fully cloud-native, serverless AWS data lakehouse, replacing a legacy platform with high technical debt.
  • Architected scalable batch and real-time ingestion pipelines using AWS Glue, DMS, and Kinesis.
  • Implemented data governance, quality, and metadata management as first-class concerns using OpenMetadata and AWS Glue Data Quality.
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Case studies

A practical view of how I approach platform problems.

Modernizing a legacy data lake into a cloud-native AWS lakehouse

A legacy data lake had grown complex, fragile, and difficult to operate, limiting the team’s ability to scale analytics and ensure data trust.

Designing event-driven orchestration for scalable data workflows

As data workflows grew in complexity, traditional schedule-based orchestration became difficult to reason about and operate.

Looking for a senior data leader who stays close to the platform?

If your team values pragmatism, long-term thinking, and engineering quality, let’s talk.