Job Role: Staff Data Engineer
Salary: Rs 3.5 Lakhs to 21.0 Lakhs
Location: Bengaluru
Company: Visa
Qualifications: Any Graduate
Experience: 1 – 3 Years
ABOUT VISA
Visa Inc. Is a global economic offerings company that allows electronic bills and economic transactions the world over. Founded in 1958 and headquartered in Foster City, California, Visa operates the sector’s largest retail electronic bills community. The company’s middle offerings include credit, debit, and pay-as-you-go card offerings, as well as price generation and protection solutions for groups and customers.
Visa’s network connects thousands and thousands of traders, economic establishments, and cardholders, enabling secure and green transactions in more than 2 hundred nations. By focusing on innovation and safety, Visa performs a pivotal function within the digital price environment, using advancements in fee technology and contributing to international financial inclusion. The organization’s commitment to evolving with the digital panorama guarantees that it stays a frontrunner in facilitating seamless and secure bills.
Job Description
As a Staff Data Engineer, you will design, construct, and optimize scalable records pipelines and structures. Collaborating with pass-useful teams, you will ensure that information is accuracy and reliable for evaluation and reporting. Your role includes imposing facts engineering great practices, developing ETL strategies, and leveraging cloud technologies to control and examine huge datasets. You will mentor junior engineers, power technical innovation, and make contributions to the strategic direction of statistics infrastructure. A strong understanding of SQL, Python, and information warehousing answers is needed, in conjunction with enjoying massive records technologies and disbursed systems.
Qualifications for a Staff Data Engineer:
Education and Experience:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- At least 5-7 years of expert experience in records engineering or a similar position.
Technical Skills:
- Proficiency in SQL and Python; reveling in different programming languages is a plus.
- Strong information on data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) and ETL strategies.
- Experience with big records technologies including Hadoop, Spark, or Kafka.
- Familiarity with cloud platforms (e.g., AWS, Google Cloud Platform, Azure) and their facts-related offerings.
- Expertise in statistics modeling, database design, and optimization strategies.
Analytical Skills:
- Strong hassle-fixing capabilities with a focal point on designing scalable and green records architectures.
- Experience in analyzing complex datasets and producing actionable insights. (Staff Data Engineer)
Soft Skills:
- Excellent communication talents, with the capacity to carry technical principles to non-technical stakeholders.
- Proven leadership and mentoring abilities, with experiance guiding junior engineers and promoting nice practices.
Project Management:
- Demonstrated capacity to control multiple initiatives concurrently while meeting time limits.
- Experience with Agile methodologies and assignment control gear is fantastic.
Responsibilities:
Data Pipeline Development:
- Design, construct, and preserve sturdy information pipelines and ETL strategies to assist records-pushed tasks.
- Ensure statistics accuracy, consistency, and reliability across various statistics resources and structures.
System Optimization:
- Optimize and troubleshoot facts structures for overall performance and performance, enforcing great practices for scalability.
- Monitor and control information infrastructure, addressing troubles proactively to limit downtime.
Collaboration:
- Work intently with data scientists, analysts, and commercial enterprise stakeholders to recognize their data wishes and translate them into technical answers. (Staff Data Engineer)
- Collaborate with engineering teams to integrate facts and answers into broader generation ecosystems.
Innovation and Improvement:
- Drive innovation with the aid of comparing and enforcing new technologies and gear to decorate information engineering practices.
- Continuously enhance statistics structures and tactics, staying abreast of enterprise developments and emerging technologies.
Mentorship and Leadership:
- Provide steering and mentorship to junior statistics engineers, fostering a tradition of continuous getting-to-know and development.
- Lead technical discussions and contribute to the strategic route of the information engineering function.
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