DescriptionThe OpportunityWe 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 OpenShift.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 PnL, 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 DoYou will play a central role in the end-to-end migration and modernisation of the data platform.Platform TransformationTranslate legacy ETL logic from SSIS and stored procedures into modern ELT pipelines using dbtImplement Data Vault 2.0 structures including Raw Vault and Business VaultBuild datamarts and curated datasets for downstream analytics and reportingOrchestration & InfrastructureDesign and operate workflows using Dagster, including scheduling, dependencies, and recovery mechanismsDeploy and run data workloads on OpenShift / Kubernetes environmentsEvent-Driven Data ProcessingEnable near real-time data processing using Kafka-triggered pipelinesIntegrate with upstream data lake environments and external data providersData Quality & ValidationEstablish robust data validation and reconciliation processesImplement automated testing and monitoring using dbtOperational OwnershipSupport production pipelines and resolve incidents when requiredCreate clear documentation and ensure operational readinessContinuously improve performance, reliability,



and maintainabilityWhat You Will DoYou will play a central role in the end-to-end migration and modernisation of the data platform.Platform TransformationTranslate legacy ETL logic from SSIS and stored procedures into modern ELT pipelines using dbtImplement Data Vault 2.0 structures including Raw Vault and Business VaultBuild datamarts and curated datasets for downstream analytics and reportingOrchestration & InfrastructureDesign and operate workflows using Dagster, including scheduling, dependencies, and recovery mechanismsDeploy and run data workloads on OpenShift / Kubernetes environmentsEvent-Driven Data ProcessingEnable near real-time data processing using Kafka-triggered pipelinesIntegrate with upstream data lake environments and external data providersData Quality & ValidationEstablish robust data validation and reconciliation processesImplement automated testing and monitoring using dbtOperational OwnershipSupport production pipelines and resolve incidents when requiredCreate clear documentation and ensure operational readinessContinuously improve performance, reliability, and maintainabilityRequirementsWhat You BringTechnical ExpertiseStrong experience with SQL Server and T-SQL, including performance optimisationProven hands-on experience with dbt in production environmentsSolid experience with workflow orchestration tools, ideally DagsterPractical knowledge of Data Vault 2.0 modelling conceptsExperience working with container platforms such as OpenShift or KubernetesFamiliarity with event-driven architectures and KafkaDomain ExperienceExperience working with financial data, ideally in banking or trading environmentsUnderstanding of risk and PnL data structures is a strong advantageWorking StyleStrong ownership mindset with the ability to work independentlyStructured, pragmatic, and delivery-focusedComfortable operating in complex and regulated environmentsClear communicator across both technical and business stakeholdersWhat Success Looks LikeWithin the first months, you will have:Delivered initial Data Vault structures and migrated datasets into the new platformEstablished stable, event-driven pipelinesEnsured data consistency and validation between legacy and new systemsContributed to a production-ready, scalable data platform

📌 Senior Data Engineer (San Luis Potosí)
🏢 Avacone
📍 San Luis Potosí