We re looking for candidates with strong technology and data understanding in big data engineering space, having proven delivery capability. This is a fantastic opportunity to be part of a leading firm as well as a part of a growing Data and Analytics team.   
    
  
   Your key responsibilities
  
  
  -   Architecting big data solutions in a cloud environment using Azure Cloud services   
-   ETL design, development, and deployment to Cloud Service   
-   Interact with Onshore, understand their business goals, contribute to the delivery of the workstreams   
-   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   
 
  
   Skills and attributes for success
  
  
  -   8+ years of experience in architecting big data solutions with proven track record in driving business success   
-   Hands-on expertise in cloud services like Microsoft Azure   
-   Experience with databricks, python, and 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   
-   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.   
-   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   
-   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   
-   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   
 
  
   To qualify for the role, you must have
  
  
  -   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 6 years hand-on experience in one or more of the above areas.   
-   Minimum 8 years industry experience