Job Details

• Design, build, Engineer, optimize and maintain conceptual and logical data models in collaboration with various stakeholders across functional as well as technical domains. Proven capability to deliver solutions to big data problems using AWS services such as Elastic compute cloud, AWS S3, AWS Data pipeline, DynamoDB, DataLake, Elastic map reduce, Redshift, Quicksight etc. Strong ability to create proposal for technological adaption and critiquing the existing technology stack to convince the stakeholders technically. Knowledge of high-availability, load-balancing and failover configurations across application, infrastructure, and platform Focus on sharing real world implementation challenges and recommend new capabilities that would simplify adoption and drive greater value from use of various cloud services especially in the AWS stack. Primary focus on performance engineering and performance architecting the database and the data stores used across various micro services implementations Fair amount of knowledge concerning micro services and the role of the data architectures pertaining to Server less micro services. Provide mentorship to team members on industry practices, technologies, and third party container solutions to build an industry-leading offering. Work with other leads to ensure that all components work together to meet objectives and performance goals as defined in the requirements. Handle multiple, competing priorities in a fast-paced, multi geographical and multi-cultural environment. Write and produce thorough technical documentation. Should be able to work in a team as well as an individual, to work under pressure and meet deadlines. Experience and Skills Sound exposure to Banking domain. Strong in Agile Development and experience with SCRUM or similar methodologies. Hands on skills in Domain driven Data modelling and Data Lake architectures. Worked on project involving current technologies and tools including, but not limited to, Core Java, Spring boot,  Micro Services, Containers, RESTful API’s, Big Data, Data Analytics, Artificial Intelligence/Machine Learning Good with Micro services, Data Driven Architectures, Algorithms, Design patterns and Anti Patterns in Data Engineering. Experience with both Relational and Non-Relational DB such as MariaDB, ScyallaDB, Cassandra, MongoDB etc. as well as integrations with Apache Kafka, Kafka Streams, Redis, AMQPs. Sound exposure to CI/CD processes using Maven and Jenkins, familiarity with GIT. Skilled to program in SQL, PL/SQL, DB optimization, Distributed Database design(portioning, sharding, compute capability allocations), programming  Experience required :- 14yrs - 18yrs(Salary open bracket)