EY EY GDS – Data and Analytics-Data Architect in Kochi, India
EY GDS – Data and Analytics-Data Architect
Requisition # KOC002LL
Post Date Apr 07, 2021
Strong understanding & familiarity with all Hadoop Ecosystem components and Hadoop Administrative Fundamentals
Strong understanding of underlying Hadoop Architectural concepts and distributed computing paradigms
Experience in the development of Hadoop APIs and MapReduce jobs for large scale data processing.
Experience in architecting big data solutions with proven track record in driving business success
Hands-on programming experience in Apache Spark using SparkSQL and Spark Streaming or Apache Storm
Hands on experience with major components like Hive, PIG, Spark, MapReduce
Experience working with NoSQL in at least one of the data stores - HBase, Cassandra, MongoDB
Experienced in Hadoop clustering and Auto scaling.
Good knowledge in apache Kafka & Apache Flume
Knowledge of Spark and Kafka integration with multiple Spark jobs to consume messages from multiple Kafka partitions
Knowledge of Apache Oozie based workflow
Hands-on expertise in cloud services like AWS, or Microsoft Azure
Experience with databricks, glue, python, step functions or ADF
Solid understanding of ETL methodologies in a multi-tiered stack, integrating with Big Data systems like Hadoop and Cassandra.
Experience with BI, and data analytics databases
Experience in converting business problems/challenges to technical solutions considering security, performance, scalability etc.
Experience in Enterprise grade solution implementations.
Knowledge in Big data architecture patterns [Lambda, Kappa]
Experience in performance bench marking enterprise applications
Experience in Data security [on the move, at rest] and knowledge of data standards like APRA, BASEL etc
Develop standardized practices for delivering new products and capabilities using Big Data technologies, including data acquisition, transformation, and analysis.
Define and develop client specific best practices around data management within a Hadoop environment on Azure cloud
Recommend design alternatives for data ingestion, processing and provisioning layers
Design and develop data ingestion programs to process large data sets in Batch mode using HIVE, Pig and Sqoop technologies
Develop data ingestion programs to ingest real-time data from LIVE sources using Apache Kafka, Spark Streaming and related technologies
Strong UNIX operating system concepts and shell scripting knowledge
Knowledge of microservices and API development
Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution.
Excellent communicator (written and verbal formal and informal).
Ability to multi-task under pressure and work independently with minimal supervision.
Strong verbal and written communication skills.
Must be a team player and enjoy working in a cooperative and collaborative team environment.
Adaptable to new technologies and standards.
Participate in all aspects of Big Data solution delivery life cycle including analysis, design, development, testing, production deployment, and support.
Minimum 8 years hand-on experience in one or more of the above areas.
Minimum 12 years industry experience