Data Analyst

Remote.AR
Remote.Colombia
Rosario
Монтевидео
Монтерей

Ако сте получили информация за тази свободна позиция от нашите рекрутери, прочетете нашата Политика за поверителност на личните данни.

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 Data Analyst to support a large scale data migration program within a capital markets environment.

This role focuses on understanding business requirements, analyzing data across legacy and target systems, and ensuring the correctness and completeness of migrated data. You will play a key role in bridging business and technology, supporting functional validation, and enabling downstream analytics and reporting.

The position requires strong analytical skills, deep understanding of data structures, and the ability to work with complex financial datasets.

Technology stack

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

Responsibilities

Work closely with business stakeholders to understand requirements and translate them into data analysis and validation tasks
Analyze legacy and target datasets to support data migration and transformation processes
Define and execute data validation and reconciliation procedures
Validate migrated data ensuring accuracy, completeness, and consistency
Document ETL processes, data mappings, and transformation logic
Write complex SQL queries to explore, validate, and analyze large datasets
Support the creation of dashboards and reports for business users
Collaborate with data engineers to ensure alignment between business rules and technical implementation
Support downstream analytics and data visualization initiatives
Identify data issues, inconsistencies, and gaps, and propose solutions

Requirements

Experience working in capital markets environments (custody, clearing, settlement, derivatives, or CCP)
Ability to translate business requirements into structured tasks for technical teams
3+ years of experience working with large data volumes and diverse data formats
Strong experience with SQL for data analysis and validation
Experience in data warehousing, dimensional modeling, reporting, and business intelligence
Experience in data schema design, data modeling, and data mappings
Strong analytical and problem solving skills

Nice to have

Experience in data migration or system transformation programs
Familiarity with AWS data services such as Glue
Experience with dbt or similar transformation tools
Experience with BI tools such as Tableau or Power BI
Understanding of data governance and data quality frameworks

Търсите сходни възможности?

Try AI chatbots with our ready-made prompt to discover similar roles that match your skills and interests.

Най-търсени позиции

1 of 1

Business Data Analyst

Remote.LATAMБразилияКолумбияМексикоУругвай

We are looking for a Business Data Analyst to join our team and support the data management ecosystem across several interconnected systems

Senior Analytics Engineer (DBT Core & Data Modeling)

GeorgiaRemote.LATAMАрменияБразилияБългарияКипърКолумбияЛатвияМексикоПолшаРумънияСърбияУругвай

The client is expanding their Product Analytics team and seeking a Data Analytics Engineer to develop data visualization dashboards in Looker. The primary objective is to enable product teams to adopt a data-driven approach by providing actionable insights, supporting hypothesis generation, and evaluating the impact of key product KPIs.