Responsibilities:

  • Own and improve data quality controls for regulatory reporting, including automated reconciliations, completeness checks, and quality gates.
  • Expand dbt model test coverage, monitor discrepancies between layers, and implement Data Contracts for critical data models.
  • Maintain role-based access control (RBAC) and Row-Level Security (RLS) across jurisdictions, including regular access reviews.
  • Enhance the data catalog through lineage collection, dataset ownership, and a business glossary of metrics.
  • Lead root-cause analysis of complex data quality incidents and improve processes to prevent recurrence.
  • Gather requirements from Business, Finance, and Compliance teams and translate them into technical specifications for Data Engineering.
  • Define and maintain data governance standards, naming conventions, model documentation, and testing rules.

Requirements:

  • Strong SQL skills, including analytical queries, query optimization, and work with large-scale datasets.
  • Hands-on dbt experience with tests, sources, and model documentation; strong Git skills.
  • Experience establishing data quality checks and metrics, and working with data catalogs such as OpenMetadata or DataHub.
  • Knowledge of access models, roles, and RLS.
  • Ability to translate business requirements into technical specifications and acceptance criteria.
  • Strong stakeholder communication and autonomy.
  • Python proficiency for automating data quality checks and interacting with metadata APIs.

Conditions and benefits:

  • Remote work with a flexible start to the workday.
  • 5/2 schedule.
  • Competitive salary determined based on interview results.
  • Fully covered sick leave and vacation; work equipment provided.
  • Benefits package covering sports, healthcare, and education.