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Staff Data Engineer

Yesterday Warsaw, Poland

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

The role offers a unique blend of Data Engineering and Machine Learning Engineering tasks, emphasizing strong software development practices. The successful candidate will collaborate with a team to conduct world-class applied data and AI project on financial payments, driving innovation in alignment with Visa's strategic vision by incubating new data- and AI-powered products and enhancing existing applications with data engineering, machine learning and AI. This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The successful candidate must have strong data, software engineering, distributed computing and machine learning skills. You will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills. 

We are looking for a skilled Engineer with expertise in both Data Engineering and Machine Learning to take ownership of our data and machine learning solutions. You will be responsible for establishing best practices in our processes - which include data management, preprocessing, code management, tool selection, distributed computing, and cloud infrastructure. Your work will be foundational to enabling our data science and ML teams to deliver at scale, reliably, and with high standards.

You will engage with different collaborators, senior executives, research scientists, software engineers and architects, as well as external parties like technology vendors, wallet providers, merchants, issuers and senior product regional managers. You will discover and propose research and development opportunities, build development plan, create, and implement the ideas.

You will have the opportunity and the responsibility to build the long-term vision for the payment industry and influence the direction of the innovation and development across Visa.

 Essential Functions

  • Lead the design, implementation, and maintenance of robust data & ML pipelines for ingesting and processing the data and training and deploying ML models.

  • Establish standards and best practices for data, code and pipeline management, versioning, and governance for ensuring reusability, scalability, and collaboration.[KI1] 

  • Evaluate, recommend, and implement tooling for data science and ML workflows, including experiment tracking, model management, and reproducibility.

  • Own the setup of distributed computing resources (on-premises or cloud, such as AWS), ensuring scalability and cost efficiency.

  • Collaborate with Data Scientists, ML Engineers, and other stakeholders to understand requirements and enable efficient model development, deployment, and monitoring.

  • Drive automation of ML pipelines (MLOps): from data ingestion and preprocessing to model training, validation, deployment, and monitoring.

  • Mentor and guide junior engineers and data scientists in engineering best practices, code reviews, and project planning.

  • Document processes, decisions, and systems to ensure maintainability and knowledge sharing within the team.

  • Stay current with industry trends and emerging technologies in data engineering, distributed computing, and MLOps.

  • Collaborate with research scientists, product owners and architects to deliver the fast-prototyping platform.

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Champion the innovation across the organizations and industries as an expert in the subject, either by providing consulting or by contributing to technology talks and presentations.

  • Make decision on trade-offs/priority during the design and execution, such as trade-off between performance and flexibility, scope and timelines, availability, and scalability, etc.

  • This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

     

    Qualifications

    Basic Qualifications
    ·5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

    Preferred Qualifications
    ·Bachelor’s, Master’s or PhD degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
    ·7+ years of directly related experience in data engineering, machine learning engineering, or related fields.
    ·Strong software engineering skills, including experience with modular code design, automated testing, code reviews, and documentation to ensure maintainable and scalable solutions.
    ·Expertise with cloud platforms (preferably AWS), especially cloud-native data and ML services.
    ·Strong understanding of algorithms and data structures.
    ·Proven experience architecting and managing data pipelines  (ETL/ELT), especially for ML/AI applications.
    ·Proven experience developing and maintaining machine learning lifecycle: data preprocessing and feature extraction, model training and evaluation, and deployment and monitoring.
    ·Excellent programming skills in Python (and optionally Scala, Java). Strong with data processing frameworks (e.g., Spark, Dask, Pandas, Airflow).
    ·Experience with distributed computing and handling of large-scale data.
    ·Hands-on experience with ML workflow tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.) and model deployment (REST APIs, containers, CI/CD).
    ·Deep knowledge of version control (git) and best practices for codebase organization in multi-person teams.
    ·Familiarity with data governance, security, and compliance standards (GDPR, HIPAA, etc. as relevant).
    ·Excellent communication and documentation skills.
    ·Demonstrated ability to take ownership and drive projects from inception to completion in a fast-paced, ambiguous environment.
    ·Familiarity with data visualization and BI tools.
    ·Contributions to open-source projects in data engineering or ML is a plus

    Additional Information

    Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

    Client-provided location(s): Warsaw, Poland
    Job ID: f006efe0-647d-41b5-9547-403dee861a7f
    Employment Type: OTHER
    Posted: 2025-07-22T12:01:24

    Perks and Benefits

    • Health and Wellness

      • Long-Term Disability
      • HSA With Employer Contribution
      • On-Site Gym
      • Health Insurance
      • Dental Insurance
      • Vision Insurance
      • Life Insurance
      • Short-Term Disability
      • Health Reimbursement Account
      • Mental Health Benefits
      • Virtual Fitness Classes
      • HSA
    • Parental Benefits

      • Fertility Benefits
      • Family Support Resources
      • Birth Parent or Maternity Leave
      • Non-Birth Parent or Paternity Leave
    • Work Flexibility

      • Flexible Work Hours
      • Remote Work Opportunities
      • Hybrid Work Opportunities
    • Office Life and Perks

      • Commuter Benefits Program
      • Company Outings
      • On-Site Cafeteria
      • Holiday Events
      • Happy Hours
      • Casual Dress
    • Vacation and Time Off

      • Paid Holidays
      • Paid Vacation
      • Volunteer Time Off
      • Summer Fridays
      • Leave of Absence
      • Personal/Sick Days
    • Financial and Retirement

      • 401(K)
      • Relocation Assistance
      • Performance Bonus
      • Stock Purchase Program
      • Company Equity
      • 401(K) With Company Matching
      • Financial Counseling
    • Professional Development

      • Shadowing Opportunities
      • Access to Online Courses
      • Promote From Within
      • Learning and Development Stipend
      • Tuition Reimbursement
      • Mentor Program
      • Leadership Training Program
      • Associate or Rotational Training Program
      • Lunch and Learns
      • Internship Program
      • Professional Coaching
    • Diversity and Inclusion

      • Diversity, Equity, and Inclusion Program
      • Employee Resource Groups (ERG)