Visa

4 weeks ago

Data Engineer (Junior - Mid Level)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Build and operate batch-oriented data pipelines and data warehousing solutions for the Open Banking AI and Data Platform domain. Translate data requirements into warehouse structures, dimensional/analytical models, and production-ready pipeline implementations that support analytics, reporting, regulatory, and AI-enabled use cases. Collaborate with product partners and platform teams to improve data quality, performance, and operational reliability, while aligning with engineering standards, security, and regulatory obligations in a hybrid work setup.

Location: Stockholm

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Develop and operate data pipelines and data warehousing solutions for the Open Banking AI and Data Platform domain.
•Implement well-structured data models and reliable batch-oriented pipelines that support analytics, reporting, regulatory, and AI-enabled use cases.
•Translate defined data requirements into warehouse structures, models, and pipeline implementations aligned with engineering standards and regulatory obligations.
•Collaborate with product partners and platform teams to ensure data is accurate, well-modelled, and production-ready.
•Continuously improve data quality, performance, and operational reliability, including data quality checks and documentation practices.

Key Requirements

•Hands-on experience implementing batch-oriented data pipelines using SQL and modern data processing frameworks.
•Experience with data warehousing solutions, including dimensional or analytical data models and schema evolution.
•Ability to contribute to data models used for analytics, reporting, and downstream data consumption.
•Familiarity with data lakes or lakehouse-style architectures.
•Proficiency with orchestration/scheduling/monitoring for reliable pipelines, plus streaming knowledge (e.g., Kafka) and at least one data engineering language (Python or Java).

Education:Bachelor's

Skills:CollaborationData quality focusOperational reliabilityDocumentationSecurity awareness

Tech Stack:SQLPythonJavaKafkaAWSGCPData lakesLakehouse

Company Brief

Visa

Global payments technology company that operates the VisaNet electronic payments network, facilitating credit, debit and digital transactions between consumers, merchants, financial institutions and governments worldwide.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1958

Glassdoor: 3.8

Website LinkedIn Glassdoor

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Visa

4 weeks ago

Data Engineer (Junior - Mid Level)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Location: Stockholm

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Develop and operate data pipelines and data warehousing solutions for the Open Banking AI and Data Platform domain.
•Implement well-structured data models and reliable batch-oriented pipelines that support analytics, reporting, regulatory, and AI-enabled use cases.
•Translate defined data requirements into warehouse structures, models, and pipeline implementations aligned with engineering standards and regulatory obligations.
•Collaborate with product partners and platform teams to ensure data is accurate, well-modelled, and production-ready.
•Continuously improve data quality, performance, and operational reliability, including data quality checks and documentation practices.

Key Requirements

•Hands-on experience implementing batch-oriented data pipelines using SQL and modern data processing frameworks.
•Experience with data warehousing solutions, including dimensional or analytical data models and schema evolution.
•Ability to contribute to data models used for analytics, reporting, and downstream data consumption.
•Familiarity with data lakes or lakehouse-style architectures.
•Proficiency with orchestration/scheduling/monitoring for reliable pipelines, plus streaming knowledge (e.g., Kafka) and at least one data engineering language (Python or Java).

Education:Bachelor's

Skills:CollaborationData quality focusOperational reliabilityDocumentationSecurity awareness

Tech Stack:SQLPythonJavaKafkaAWSGCPData lakesLakehouse

Company Brief

Visa

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1958

Glassdoor: 3.8

Website LinkedIn Glassdoor