Research and analyze emerging technologies, platforms, tools and solutions; map new and existing business opportunities to potential big data, intelligence and analytics solutions
Capture business/functional requirements, expected service levels and user experience requirements from business units
Provide recommendations, technical direction and leadership for the selection and incorporation of cloud based big data warehouse and data lake solutions and business applications
Develop effective phased roadmap and practical architectures for deploying modern enterprise data warehouse and data lake platforms for business intelligence, advanced analytics, machine learning and data science applications
Plan, architect and build next-generation enterprise data lake and analytics applications using the Hadoop platforms (ecosystem technologies) like Azure HDInsight, Cloudera, Hortonworks, MAPR
Develop highly scalable, extensible and reliable big data solutions that enable collection, storage, modeling, and analysis of large structured / un-structured datasets from multi-channel sources
Develop and maintain processes to acquire, analyze, store, cleanse, and transform large datasets using tools like Spark, MapReduce, Kafka, Sqoop, Hive, NiFi, HBASE, YARN etc.
Apply strong expertise on ETL architectures, data movement technologies, data cleansing techniques, optimization of datastores, and building communication channels between structured and unstructured databases to support solution operationalization
Develop and maintain enterprise data standards, quality guidelines, best practices, security policies and governance processes for the Big-Data / Hadoop ecosystem
Apply strong understanding of cloud or on-premise infrastructure architectures, environments, constraints, and available options for big-data warehouses and data-lakes; develop solution deployment roadmap and architectures with cloud/infrastructure teams
10+ years of hands-on experience in architecture, design or development of enterprise data solutions, applications, and integrations
4+ years of demonstrated experience in architecture, data modelling and implementation of large, scalable, and highly complex big data warehouse and data lake projects using cloud-native and open-source platforms and technologies
Demonstrated expertise and hands-on experience with Hadoop ecosystem platforms (like Azure HDInsight, Cloudera, Hortonworks, MAPR) and NoSQL datastores (HBase, Cassandra, Azure CosmosDB)
Demonstrated expertise and hands-on experience with Azure & AWS based big data technologies like Azure SQL Data Warehouse, Azure Data Lake, Azure ML Studio/Workbench, Databricks, Cortana Intelligence Suite, Redshift, RDS, Glacier, Kinesis etc.
Advanced level proficiency and hands-on scripting experience with Spark, Python, U/SQL etc.; Advanced level proficiency in R, PySpark, SparkR, Scala, Hive
Hands-on expertise working with large complex data sets, real-time/near real-time analytics, and distributed big data platforms; Experience in deploying data movement, storage and cleansing, transformation and data quality management for big data solutions
Excellent communication skills – writing, presentations, interpersonal skills
B.S. Engineering or Computer Science is preferred; advanced certifications in big data, machine learning and advanced analytical platforms etc. is desirable.