Data Engineer

Remote.AR
Remote.Colombia
Rosario
Монтевідео
Монтеррей

Якщо ви отримали цю вакансію від наших рекрутерів, ознайомтеся з нашою Політикою про конфіденційність.

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 Middle Data Engineer to support a complex data migration program by building, optimizing, and maintaining scalable data pipelines. You will work closely with data architects and analysts to ensure data is processed efficiently, reliably, and in line with business and regulatory requirements in a cloud environment.

This role focuses on building, optimizing, and maintaining data pipelines that enable the extraction, transformation, and loading of large volumes of data from legacy systems into a modern data platform. You will work closely with data architects and analysts to ensure data is processed efficiently, reliably, and in alignment with business requirements.

The position requires strong hands on experience with data processing tools, attention to data quality, and the ability to work with complex datasets in a cloud environment.

Technology stack

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

Responsibilities

Design, build, and maintain ETL/ELT pipelines using AWS Glue and dbt
Extract and process data from legacy systems, ensuring efficient and scalable transformations
Collaborate with data architects to implement target data models and transformation logic
Work with data analysts to ensure data availability and correctness for validation and reporting
Optimize data pipelines for performance, scalability, and cost efficiency
Ensure data quality through validation checks, logging, and monitoring mechanisms
Handle large volumes of structured data across multiple sources and systems
Implement and maintain data workflows following best practices in version control and CI/CD
Troubleshoot data issues and support root cause analysis across the data pipeline
Document data pipelines, transformations, and technical processes

Requirements

Strong experience with SQL for data transformation and querying
Hands on experience with AWS Glue and cloud based data processing
Experience building and maintaining ETL/ELT pipelines
Experience with dbt or similar transformation frameworks
Experience working with large scale data processing and data pipelines
Familiarity with Git and CI/CD practices
Understanding of data modeling concepts and data warehouse architectures
Strong problem solving skills and attention to detail

Nice to have

Experience working in capital markets environments
Experience with Oracle databases and legacy system integrations
Familiarity with performance optimization in data pipelines
Experience with monitoring, logging, and observability in data systems
Exposure to data migration or large scale transformation programs

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We offer

Відпустка

Згідно з законом вашої країни. Ми просимо обов'язково відпочити по-справжньому

Страхування

Допомагаємо оформити страховку вам і вашим близьким

Оплата лікарняних

10 днів без довідок від лікарів, далі — за законом вашої країни

Рівні можливості

Відпочинок на свята

За офіційним календарем незалежно від клієнта

Приємна обстановка

Два великі корпоративи та багато маленьких свят для колег

Служба комфорту

Розв’язання технічних і побутових проблем на роботі

Детальніше про приємне Перелік переваг у PDF

Дуже потрібні

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