Staff Data Engineer-Scala/Big Data-6+yrs Visa
Visa
Office Location
Full Time
Experience: 3 - 3 years required
Pay:
Salary Information not included
Type: Full Time
Location: All India
Skills: Java, Scala, Python, Hadoop, spark, hive, Kafka, Db2, MS SQL, MySQL, NoSQL, Jenkins, Artifactory, Power Bi, APIs, Docker, Kubernetes, Rest Services
About Visa
Job Description
Job Description: Visa is looking for a Staff Data Engineer to join the Data Platform department and contribute to the Data as a Service organization. In this role, you will focus on the design, architecture, and coding of one or more DaaS solutions. Your primary responsibilities will include developing large-scale multi-tenant software components within the DaaS team. Collaboration with stakeholders and Product owners will be a key aspect of this position. This is a hybrid role, and the specific in-office requirements will be communicated by your hiring manager. Qualifications: Basic Qualifications: - A minimum of 6 years of relevant work experience with a Bachelor's Degree or 3 years of experience with an Advanced Degree (e.g., Masters, MBA, JD, MD) or 2 years of work experience with a PhD. Preferred Qualifications: - Bachelor's or Master's degree in Computer Science or related fields. - At least 4 years of experience in developing data-driven business solutions and addressing data challenges. - Minimum of 3 years of experience in constructing large-scale data solutions using open-source technologies, with proficiency in Big Data tools like Hadoop, Spark, Hive, and Kafka. - Hands-on expertise of at least 3 years in Java, Scala, or Python. - Familiarity with highly distributed, scalable, concurrent, and low-latency systems, working with databases like DB2, MS SQL, MySQL, and NoSQL. - Desirable experience with Continuous Integration tools such as Jenkins, Artifactory, etc. - Exposure to data visualization and business intelligence tools like Power BI is a plus. - Knowledge of building REST services and APIs following best practices, as well as experience with Docker and Kubernetes, would be advantageous.,