Description The Opportunity
We are supporting a major
data platform transformation within a banking environment , moving from a legacy SQL Server and SSIS-based setup to a modern, scalable architecture built on
dbt, Dagster, and Open Shift. This role is not about maintaining existing systems. It is about
rebuilding a critical data platform from the ground up , with direct impact on
risk, trading Pn L, and core financial data flows. We are looking for a
hands-on Senior Data Engineer
who can take ownership of complex migration workstreams and deliver reliably in a regulated, high-stakes environment.
What You Will Do
You will play a central role in the
end-to-end migration and modernisation
of the data platform. Platform Transformation Translate legacy ETL logic from SSIS and stored procedures into modern
ELT pipelines using dbt Implement
Data Vault 2.0 structures
including Raw Vault and Business Vault Build
datamarts and curated datasets
for downstream analytics and reporting
Orchestration & Infrastructure Design and operate workflows using
Dagster , including scheduling, dependencies, and recovery mechanisms Deploy and run data workloads on
Open Shift / Kubernetes environments
Event-Driven Data Processing Enable
near real-time data processing
using Kafka-triggered pipelines Integrate with upstream data lake environments and external data providers
Data Quality & Validation Establish robust
data validation and reconciliation processes Implement automated testing and monitoring using dbt
Operational Ownership Support production pipelines and resolve incidents when required Create clear documentation and ensure operational readiness Continuously improve performance, reliability, and maintainability
What You Will Do
You will play a central role in the
end-to-end migration and modernisation
of the data platform.
Platform Transformation Translate legacy ETL logic from SSIS and stored procedures into modern
ELT pipelines using dbt Implement
Data Vault 2.0 structures




including Raw Vault and Business Vault Build
datamarts and curated datasets
for downstream analytics and reporting
Orchestration & Infrastructure Design and operate workflows using
Dagster , including scheduling, dependencies, and recovery mechanisms Deploy and run data workloads on
Open Shift / Kubernetes environments
Event-Driven Data Processing Enable
near real-time data processing
using Kafka-triggered pipelines Integrate with upstream data lake environments and external data providers
Data Quality & Validation Establish robust
data validation and reconciliation processes Implement automated testing and monitoring using dbt
Operational Ownership Support production pipelines and resolve incidents when required Create clear documentation and ensure operational readiness Continuously improve performance, reliability, and maintainability
Requirements What You Bring
Technical Expertise Strong experience with
SQL Server and T-SQL , including performance optimisation Proven hands-on experience with
dbt
in production environments Solid experience with
workflow orchestration tools , ideally Dagster Practical knowledge of
Data Vault 2.0 modelling concepts Experience working with
container platforms such as Open Shift or Kubernetes Familiarity with
event-driven architectures and Kafka
Domain Experience Experience working with
financial data , ideally in banking or trading environments Understanding of
risk and Pn L data structures
is a strong advantage
Working Style Strong ownership mindset with the ability to work independently Structured, pragmatic, and delivery-focused Comfortable operating in complex and regulated environments Clear communicator across both technical and business stakeholders
What Success Looks Like
Within the first months, you will have: Delivered initial
Data Vault structures and migrated datasets
into the new platform Established
stable, event-driven pipelines Ensured
data consistency and validation
between legacy and new systems Contributed to a
production-ready, scalable data platform

📌 Senior data engineer (Mérida)
🏢 Avacone
📍 Mérida