Senior Data Engineer

Monterrey
Montevideo
Remote.AR
Remote.Colombia
Rosario

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Project overview

The program is a multi phase data migration initiative aimed at replacing legacy capital markets systems with a modern platform ecosystem. It includes the migration of critical datasets across custody, clearing and settlement, derivatives processing, and CCP operations. The project spans 18 months and follows an incremental approach with strong emphasis on data integrity, reconciliation, and traceability.

Team

You will work within a cross functional team including data engineers, data analysts, and domain experts from capital markets.

The team operates under an iterative delivery model, with strong emphasis on data validation cycles, reconciliation processes, and collaboration with business stakeholders to ensure correctness of migrated data.

Position overview

We are looking for a Senior Data Engineer to lead the development and optimization of data pipelines within a large scale data migration program in a capital markets environment.

This role is responsible for designing and implementing robust, scalable, and production grade data pipelines, ensuring data quality and consistency across multiple systems. You will play a key role in shaping the data processing layer, guiding best practices, and supporting the successful migration of critical financial data.

The position requires strong technical expertise, architectural thinking, and the ability to mentor other engineers while collaborating closely with data architects and business stakeholders.

Technology stack

SQL, AWS Glue, dbt, Oracle, AWS, Git

Responsibilities

Design and implement scalable, reliable, and maintainable ETL/ELT pipelines using AWS Glue and dbt
Define and enforce best practices for data engineering, including coding standards, testing, and deployment
Lead the integration of data from multiple legacy systems into the target platform
Ensure data quality, consistency, and integrity across all stages of the data pipeline
Collaborate with data architects to implement target data models and transformation strategies
Optimize data pipelines for performance, scalability, and cost efficiency
Implement robust error handling, logging, and monitoring mechanisms
Guide and mentor mid level engineers, providing technical direction and code reviews
Work closely with data analysts and business stakeholders to ensure data meets functional requirements
Troubleshoot complex data issues and drive root cause analysis
Contribute to the design of the overall data platform and processing architecture
Document data pipelines, standards, and technical decisions

Requirements

Strong expertise in SQL and data transformation at scale
Extensive experience with AWS Glue and cloud based data processing
Proven experience building production grade ETL/ELT pipelines
Strong experience with dbt or similar transformation frameworks
Experience working with large volumes of data in complex environments
Strong understanding of data modeling and data warehouse architectures
Experience implementing CI/CD practices in data environments
Experience designing scalable and maintainable data solutions
Strong problem solving skills and attention to detail

Nice to have

Experience in capital markets (custody, clearing, settlement, derivatives, CCP)
Experience in large scale data migration or transformation programs
Experience with Oracle based legacy systems
Familiarity with data governance, data lineage, and metadata management
Experience with observability tools and monitoring frameworks

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