Senior Data Engineer

Visa Visa · Fintech · Stockholm, Sweden, Sweden

Senior Data Engineer role focused on designing, building, and evolving a next-generation data platform for Visa's Open Banking domain. Responsibilities include data warehousing, real-time/batch processing, analytical event systems, data modeling, and infrastructure management, with a strong emphasis on security, compliance, and regulatory requirements (GDPR, PSD2). The role involves collaboration with various teams, architectural design, and mentoring junior engineers. Familiarity with AI/ML data pipelines is mentioned.

What you'd actually do

  1. designing, building, and evolving our next‑generation data platform
  2. work hands‑on with complex data systems that support a wide range of use cases, including data warehousing, real‑time and batch data processing, analytical event systems, advanced data modelling, and infrastructure management
  3. collaborate closely with engineers, product managers, and partners across engineering, compliance, and AI to deliver secure, compliant, and scalable data solutions that meet the needs of the Open Banking landscape
  4. contribute to architectural design discussions, apply established patterns and standards, and help ensure that solutions meet performance, reliability, security, and regulatory requirements
  5. take ownership of complex technical problems, deliver high‑quality and maintainable solutions, and support less‑experienced engineers through technical guidance and knowledge sharing

Skills

Required

  • data engineering
  • data architecture
  • data warehousing
  • ETL/ELT pipelines
  • data lakes in enterprise environments
  • building secure, compliant, and resilient data systems
  • privacy and regulatory requirements such as GDPR and PSD2
  • data processing frameworks and languages (e.g. Spark, Hadoop, SQL, Python/Scala/Java)
  • event driven or streaming platforms (e.g. Kafka, Kinesis)
  • data modelling
  • schema design
  • master data concepts
  • metadata management
  • cloud platforms (e.g. AWS, Azure, GCP)
  • containerization (Docker, Kubernetes)
  • Infrastructure as Code tools (e.g. Terraform, CloudFormation)
  • AI/ML data pipelines
  • supporting machine learning workloads in production environments
  • work independently on complex technical tasks
  • contribute to design decisions
  • deliver solutions end to end
  • communication and collaboration skills
  • explain technical concepts to both technical and non technical stakeholders
  • Relevant degree in Computer Science, Engineering, Information Systems, or a related field

Nice to have

  • Professional certifications

What the JD emphasized

  • secure, compliant, and scalable data solutions
  • regulatory requirements
  • privacy and regulatory requirements such as GDPR and PSD2
  • AI/ML data pipelines and supporting machine learning workloads in production environments