Job Title: Sr. Data Engineer
Salary: 19.8 Lakhs per year (₹1.6L per month).
Location: Bengaluru
Company: Visa
Qualifications: Any Graduate
Experience: 1 – 2 Years
ABOUT VISA
Visa Inc. Is a worldwide leader in virtual bills technology, facilitating steady and handy transactions for purchasers, businesses, and governments. Founded in 1958, Visa operates a sizeable network that connects cardholders, traders, and financial establishments throughout the globe. The company’s middle services consist of credit score, debit, and pay-as-you-go card services, together with superior charge answers like contactless and cell payments.
Visa’s network is renowned for its reliability and security, using trendy generations to shield against fraud and make certain seamless transaction processing. Headquartered in Foster City, California, Visa is devoted to innovation, using the destiny of charge generation, and expanding economic inclusion. Its various portfolio also consists of numerous fee-introduced offerings such as fraud prevention tools, facts analytics, and loyalty applications, aimed at enhancing the general payment enjoy. Through partnerships and collaborations, Visa keeps to guide the manner in transforming the global bills panorama.
Job Overview
A Senior Data Engineer is responsible for designing, growing, and maintaining scalable facts pipelines and architectures. They manipulate massive datasets, make certain records excellent and integrity, and collaborate with facts scientists and analysts to deliver actionable insights. The position entails optimizing information storage and retrieval, implementing information safety features, and leveraging superior analytics gear. Strong proficiency in programming languages like Python or Java, enjoyment of big statistics technologies (e.g., Hadoop, Spark), and understanding of database control structures are critical. The function demands hassle-fixing competencies and the capability to work in a dynamic environment.
Role and Responsibilities For Sr. Data Engineer:
- Data Pipeline Development: Design and put in force scalable and efficient facts pipelines to process big volumes of statistics from various assets. Ensure that information flows smoothly from supply to destination, meeting exceptional performance standards.
- Data Architecture: Develop and preserve information architectures that aid enterprise analytics and reporting wishes. This includes growing records models, coping with statistics warehouses, and integrating numerous information sources.
- Performance Optimization: Optimize records storage and retrieval procedures for speed and efficiency. Identify and remedy bottlenecks in information processing and make certain that structures cope with massive-scale statistics with minimum latency.
- Data Quality and Integrity: Implement and implement facts governance policies to ensure facts accuracy, consistency, and reliability. Regularly display statistics best and address any problems that stand up.
- Collaboration: Work closely with statistics scientists, analysts, and other stakeholders to apprehend records necessities and deliver answers that meet commercial enterprise needs. Provide help for facts-associated queries and troubleshooting. (Sr. Data Engineer)
- Technology Integration: Integrate and deploy new records technology and equipment as required. Stay contemporary with enterprise traits and improvements to make sure that the enterprise’s data infrastructure remains cutting-edge.
- Security and Compliance: Implement records security measures to shield sensitive records. Ensure that statistics managing practices observe applicable rules and standards.
- Documentation and Reporting: Maintain comprehensive documentation for facts structures, tactics, and workflows. Generate reviews on information infrastructure performance and undertaking development.
Skills For Sr. Data Engineer:
- Technical Expertise: Proficiency in programming languages including Python, Java, or Scala. Deep expertise in large data technology (e.g., Hadoop, Spark) and information storage answers (e.g., SQL, NoSQL databases).
- Data Modeling: Strong abilities in designing and imposing records fashions, records warehousing, and ETL processes.
- Analytical Skills: Ability to research complicated facts and structures and identify areas for development. Strong hassle-fixing abilities to address technical challenges.
- Performance Tuning: Experience in optimizing facts workflows and machine overall performance.
- Collaboration: Excellent verbal exchange and teamwork talents to work efficiently with go-useful groups. (Sr. Data Engineer)
- Project Management: Ability to manipulate more than one project and meet closing dates whilst maintaining top-notch requirements.
- Security Knowledge: Understanding of records security practices and compliance necessities.
- Adaptability: Willingness to examine new technologies and adapt to evolving records necessities.
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