Technical Lead

Role overview

Technical Lead at Infinite Computer Solutions

Employment details

• Location: Bangalore

Benefits

• Have good exposure to Healthcare domain

Additional role details

• Interaction with business users/stakeholders and requirement gathering, Involved Functional Requirement Specifications from customer and understand the same.
• Good understanding and real time architecture experience on Hadoop ecosystem (HDFS, Map Reduce, YARN, Hive, Sqoop, Spark) and Azure cloud (ADLS, ADFS, ADF)
• Should have real time experience by using various file formats (csv, parquet, text file, avro, sequential file)
• Should have Hands-on experience with hive internal, external tables, hive join techniques, partitions, bucketing and hive optimization techniques
• Should have hands-on experience in developing Spark applications using Data frame API, Spark-SQL in Data bricks for data extraction, transformation, and aggregation from multiple file formats for Analyzing & transforming the data using Scala and Python to uncover insights into the customer usage patterns.
• Should have hands-on experience Extract Transform and Load data from sources Systems (On-prem) to Azure Data Storage services using a combination of Azure Data factory, T-SQL, Spark SQL.
• Should have hands-on Experience metadata driven ingestion pipeline framework by using Azure Data Factory
• Should have real time experience on implementing spark optimization techniques and adaptive query execution configuration in data bricks
• Should have good analytics and writing SQL queries to consume data and generate reports using Power BI
• Added advantage bash script experience with text file processing skills using Regex, Sed, Awk, Grep, curl, etc.
• Cloudera Manager - Monitor jobs and query performance. customizable dashboard, with the ability to create advanced charts for historical monitoring.
• Query on Impala nodes to find all the error (Failed queries, Missing Stats, out of memory exception)
• Monitoring entire cluster and find memory utilization based on resource level.
• Workload XM - monitor the workload, memory, resource utilization, slow job and failed job, queries in spark jobs and impala queries
• Involved in conducting the code review and Results with the Developers