technologies-expected :

technologies-optional :

responsibilities :

Analyse and troubleshoot data across complex financial data pipelines to ensure consistency and accuracy between multiple sources
Work with modern data stack tools such as dbt (data modeling) and Airflow (orchestration) to build, maintain, and enhance data pipelines
Investigate and resolve data quality issues (e.g., missing or inconsistent data across systems and reports)
Contribute to data model design and enhancements within existing pipelines, including backfilling historical data
Collaborate closely with data engineers and other analysts on shared ownership of data pipelines and applications
Work with APIs and data ingestion processes, including testing and validating data flows (e.g., using Postman)
Operate within Git-based workflows (GitLab), including version control and CI/CD processes
Support reporting and analytics use cases by preparing datasets and, where needed, building dashboards
Participate in Agile ceremonies and iterative delivery of data solutions

requirements-expected :

Strong SQL skills and experience working with complex datasets
Hands-on experience or willingness to work with dbt for data modeling
Experience with cloud data environments (GCP)
Experience working with orchestration tools (e.g., Airflow) or similar concepts
Experience with infrastructure-as-code tools (e.g., Terraform)
Familiarity with Git and collaborative development workflows
Ability to investigate data issues across multiple systems and identify root causes
Basic scripting skills (Python) and understanding of API-based data flows
Experience with BI tools (Tableau, Power BI, Looker, or similar)
Understanding of financial instruments (equities, derivatives, FX, etc.)
Strong communication skills and ability to collaborate in cross-functional teams
Experience working in Agile environments (Scrum or Kanban)

technologies-optional :