Data Engineer

Visa Visa · Fintech · Stockholm, Sweden, Sweden

The Data Engineer will contribute to the development and operation of data pipelines and data warehousing solutions within the Open Banking AI and Data Platform domain. The role focuses on implementing well-structured data models and reliable batch-oriented data pipelines that support analytics, reporting, regulatory, and AI-enabled use cases, in alignment with Visa engineering standards, security requirements, and regulatory obligations.

What you'd actually do

  1. Contributes to the development and operation of data pipelines and data warehousing solutions within the Open Banking AI and Data Platform domain.
  2. Focuses on implementing well-structured data models and reliable batch-oriented data pipelines that support analytics, reporting, regulatory, and AI-enabled use cases, in alignment with Visa engineering standards, security requirements, and regulatory obligations.
  3. Effectively translates defined data requirements into warehouse structures, data models, and pipeline implementations.
  4. Collaborates closely with peers, product partners, and platform teams to ensure data is accurate, well-modelled, and production-ready, while contributing to the ongoing improvement of data quality, performance, and operational reliability.

Skills

Required

  • Hands-on experience implementing batch-oriented data pipelines using SQL and modern data processing frameworks.
  • Practical experience working with data warehousing solutions, including implementing dimensional or analytical data models and supporting schema evolution.
  • Experience contributing to data models that support analytics, reporting, and downstream data consumption.
  • Familiarity with data lakes or lakehouse-style architectures.
  • Experience using orchestration, scheduling, and monitoring tools to support reliable data pipelines.
  • Working knowledge of event-driven or streaming platforms (e.g. Kafka), primarily in support of analytical or warehousing use cases.
  • Proficiency in one or more programming languages commonly used in data engineering (e.g. Python, Java).
  • Experience working within cloud environments (AWS or GCP).
  • Understanding of data quality checks, basic lineage concepts, and documentation practices.
  • Awareness of data security, privacy, and compliance considerations (e.g. GDPR).
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

What the JD emphasized

  • regulatory obligations
  • regulatory