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
- 8-11 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 8 years hand-on experience in one or more of the above areas.
- Minimum 8 years industry experience
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