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Visa

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3.6

based on 339 Reviews

97 Visa Jobs

Staff Data Engineer, Data Engineering

Visa Inc

3.6

based on 339 Reviews

8-13 years

₹ 45 - 67.125L/yr (AmbitionBox estimate)

Bangalore / Bengaluru

1 vacancy

Staff Data Engineer, Data Engineering

Visa

posted 5hr ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analysis Data Analytics Consulting Linux Administration Financial Services Agile Coaching

+ 3 more

Job Description

Design: Lead the data pipeline designs as per the defined architecture of the metric repository, using/building re-usable functions and frameworks ensuring scalability, reliability and performance.
Data Analysis: Understand the metric definitions, perform the analysis and lead the discussions with the requestors from across the regions to define the calculation logic and mapping from the source data assets
Data Pipeline Development: Lead a team of data engineers to develop end to end data pipelines to create the new metrics of the metric repository and re-engineer scripts created by the data science teams, such that they can be easily plugged into existing ML Ops frameworks.
AI/ML: Design and develop the integration of the AI/ML model outputs into the metric repository, build the ML Ops components to support and manage the lifecycle of AI based models built by the regional and global data science teams.
Data Quality and Governance: Ensure and enforce the defined data quality standards around data accuracy, integrity and consistency across all deliverables and client deliveries.
Code Review and Best Practices: Conduct code reviews and ensure adherence to best practices in development and deployment. Define and build technical documentation and adherence to the CI/CD processes.
Operations: Support the generation and delivery of Insight feeds to clients, on-time and with the required data quality checks.
Team Management & Collaboration: Collaborate with Data engineers, Data scientists and various groups within the organization to identify areas of improvement, bottlenecks and re-use existing frameworks/processes.

Technical skills

Experience in building large globally applicable data platforms using different data modelling, data storage and data flow techniques to support the technical and business use cases and a solid understanding of best practices in data engineering
Experience with machine learning model inference, validation, deployment and management of BAU operations.
Strong programming skills in building data pipelines using PySpark, Hive, Airflow.
Experience working with scheduling tools (Airflow, Oozie) or building data processing orchestration workflows.
Hands-on experience working with large scale data ingestion, processing, and storage in the Hadoop ecosystem
Experience in writing and optimizing SQL queries in Big data environment.
Experience in creating data dictionaries, setup and monitor data validation alerts, and execute periodic jobs to maintain data pipelines for completed projects
Experience working in Linux/Unix environment and exposure to command line utilities.
Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.
Experience working in building and integrating the code in the defined CI/CD framework using git.
Experience in drafting solution architecture frameworks that rely on API s and micro-services

Strategic and Functional Excellence

Good business acumen to orient data analysis to business needs of clients, including experience in the payments space.
Ability to translate data and technical concepts into requirements documents, business cases and user stories.
Good understanding of agile working practices and related program management skills.
Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.
Excellent communication and presentation skills with ability to interact with different cross-functional team members at varying levels
Ability to learn new tools and paradigms as data science continues to evolve at Visa and elsewhere.

Basic Qualifications
-8+ years of relevant work experience with a Bachelor s Degree or 7+ years of
relevant work experience with a Masters or Advanced Degree with specialization
in Computer science, Information science, Data Engineering and Analytics or
relevant area.

Preferred Qualifications
-5+ years of experience around development of centralized data repositories
Familiarity with shared services, consulting, financial services is a strong plus

Employment Type: Full Time, Permanent

Read full job description

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People are getting interviews at Visa through

(based on 66 Visa interviews)

Job Portal

Campus Placement

Referral

Company Website

Walkin

Recruitment Consultant

33%

23%

18%

12%

9% candidates got the interview through other sources.

High Confidence

What people at Visa are saying

2.7

Rating based on 8 Data Engineer Staff reviews

Anonymous · Business Intelligence & Analytics in Bengaluru

Likes

The only good thing about Visa Banglore is the cafeteria everything else is a failure

Dislikes

Clueless upper and middle management, Its like a distillation of incompetence, Everyone even mediocrely good has either quit or has been fired, Managers if you are competent look at you as a threat, Greatest sin is questing them, you can forget about you review and hikes then. if you are idiot you are welcomed and offered anything you want

Read 8 reviews