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Job Location: Bangalore/Bengaluru
Youll bring this to the table
- Experience in driving solution architecture, planning infra, building large scale and secure data analytics applications Ability to create technical architecture for modern data platforms with considerations such as business technology landscape, functional and nonfunctional requirements, right tool sets, etc.,
- End to end implementation experience in data analytics solutions (data ingestion, processing, provisioning and visualization) for largescale and complex environments
- Experience working with data pipelines, distributed computing platforms, cloud platforms, visualization tools, supporting BI and data science consumers, exposure to supporting AIML use cases
- Handsonexperience developing enterprise solutions using designing and building frameworks, enterprise patterns, database design and development
- End to end Cloud solution on AWS (EC2, S3, EMR, Spectrum, Dynamo DB, RDS, Redshift, Glue, Kinesis) Azure (Azure SQL DW, Azure Data factory, HDInsight, Cosmos DB, PostgreSQL, SQL on Azure) Understanding of Design patterns (Lamdba architectureData lakemicro services)
- End to end Big data solution on ClouderaHortonworksMapR Realtime solution using Spark streaming, KafkaApache pulsarKinesis Batch solution and distributed computing using ETLELT (SSISInformaticaTalendSpark SQLSpark Data frameAWS GlueADF) Distributed compute solution (SparkStormHiveImpala) Functional solutions
- Identify the use cases and define solutions which will result in value revenuesavings to customers Distributed storage and NoSQL storage (Cassandra, Mongo DB, Datastax) Languages (Python, Scala) DWBI (MSBI, Oracle, Teradata), Data modeling, performance tuning, memory optimizationDB partitioning Frameworks, reusable components, accelerators, CICD automation Data governance using Apache atlas, Falcon, Ranger, Erwin, Metadata manager Evaluate and recommend alternate architectural patterns, technology stack and components tool options.
- Proficiency in data modelling, for both structured and unstructured data, for various layers of storage Mentor and lead a data engineering teams to design, develop, test and deploy high performance data analytics solutions Collaborate with Scrum Master and PMO to organize deliverables into phases and sprints; drive estimation and sizing, contribute actively to planning and scheduling the solution implementation
- Define best practices, standards, processes for cloud and data engineering implementation.
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