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Khader Basha Email & Phone Number

Technical Lead - Azure Data Engineering at Capgemini
Location: Chennai, Tamil Nadu, India 5 work roles
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Role
Technical Lead - Azure Data Engineering
Location
Chennai, Tamil Nadu, India
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Khader Basha is listed as Technical Lead - Azure Data Engineering at Capgemini, a with 321265 employees, based in Chennai, Tamil Nadu, India. AeroLeads shows a matched LinkedIn profile for Khader Basha.

Khader Basha previously worked as Technical Lead Data Engineer at Capgemini and Senior Data Engineer in Cognizant Technology Solutions Pvt Ltd at Cognizant.

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About Khader Basha

Collaborative engineering professional with substantial knowledge and experience in Analysis, Design, Development, Implementation, migration, convergence, Manage, implementation, and Support of large DBs, Data-warehouse/Data Lake, and Big Data systems by creating intuitive architectures and frameworks that help organizations effectively capture, store, process and analyze huge volume of data. Skilled in Big Data, Pyspark and Azure. As a Senior Data Engineer, I develop and deploy scalable and robust big data applications using Synapse, Pyspark, and Devops Pipeline and analyst to provide data-driven insights and solution for various clients across industries and domains. 7+ years of professional work experience in the field of Data Engineering with a proven track record in designing, implementing and optimizing robust big data infrastructure and Azure Pipelines. Strengths:Being through the evolution of Data Products into the most innovative data platform in the Azure Cloud blending Data Lake, Data Integration, Real-Time Processing, Services Oriented Architecture, Data Ingestion, Transformation, Loading into delta table, Data Platform Management and Data Engineering!Involved on :Cloud - Azure Data stack: ETL pipeline, ADLS, Azure Synapse, ADF,ADB and SQL, Datamart, PysparkData Processing BigData - Hadoop, PysparkDatabases - SQL, Data Warehouse - Dimensional/Fact modelingResponsibilities as Azure Data Engineer:1. Provide technical thought leadership on Azure cloud data analytics strategy, adoption, and design.2. Develop the code as per the business requirements and create the Azure synapse Pipeline, for orchestrate the job and develop the code by using Notebook by using Azure Synapse Analytics stored in ADLS.3.High proficient in Azure data technologies including Azure Data Factory, Databricks, Azure Synapse Analytics. Strong proficiency in SQL/Datamart and complex queries Deep experience in Data Analysis, including source data analysis, data profiling and mapping. Good experience in building data pipelines using ADF/ Azure Databricks, Synapse, PySpark, Proven hands-on experience with a large-scale data warehouse. Hands-on data migration experience from legacy systems to new solutions, such as from on-premises clusters to Cloud. Technically skilled in:1. Microsoft Azure:• ADF/ADB and Azure Synapse• Azure Data Lake Store Gen 2/Azure Storages2. Big Data Engineering: • Apache Spark• Hadoop3. Programming Languages:• Python• Unix Shell Scripting• Scala4. Job Schedulers:• Oozie/Azure Triggers6. Code Repositories:• GitHub . Azure Devops

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Capgemini
Capgemini
Technical Lead - Azure Data Engineering
Chennai, TN, IN
Website
Employees
321265
AeroLeads page
5 roles

Khader Basha work experience

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Technical Lead - Azure Data Engineering

Chennai, Tn, In

Technical Lead Data Engineer

• Designed and developed Enterprise Data lake and Data Refinery for Synchrony clients.• Attending scrum call on a daily basis. Working closely with an Onsite counterpart for the story created for me for the coming sprint release.• Pull the latest code from Bitbucket, clone the repo for our feature branch by using Git and start development and design activity based on requirements by using Hadoop, Hive and Spark Dataframe/Dataset.• Worked on legacy code decommission from existing Hive RDZ layer zone. I have removed RDZ layer related code from the Collections random digits application and test it in the lower environment. Legacy Hive table deletion worked on HQL scripts and execution. • Successfully completed Data ingestion for 2021-year data and from the production and execute the Spark job scripts and validated the logs end to end.• Successfully completed 2019 data ingested and do the Schema validation/analysis done from the source code and the source files for the 2019 year.• To test the code, I will be building the jar and doing some valuation date modifications in properties file and execute the respective repo one-time script end to end Spark jobs. Monitor the logs for respective spark jobs in SparkUI.• Lead a 6-member team members and make sure the task should deliver on time. • Involved end to end testing and creating the test cases/logs for decouple and Collection Gemfire process application as per the business requirements.• Involved in DR activity performed HDFS folder creation, testing and application validation functionality check. • Mentoring and providing guidance to team members• Collaborating with customers, Architects, and onsite/offshore development teams• Designed Hive repository with external tables, internal tables, buckets, partitions, UDF, and ORC compressions for incremental data load of parsed data for analytical & operational dashboards

Senior Data Engineer In Cognizant Technology Solutions Pvt Ltd

Chennai, Tamil Nadu, India

Having 4+ years of experience in Full stack Bigdata Engineering. Having good exposure in Banking, Insurance, and HealthCare domains.Roles and Responsibilities: • Development and analysis on major components in Hadoop Ecosystem like HDFS, YARN, Hive, Hbase-Hive Integration, Sqoop, Scala, Python, Spark Core, SQL and Streaming, Kafka, Elastic Search, Apache NIFI, Oozie, and Azure.• Worked on improvising the tuning options using HIVE functions such as Partitioning, Bucketing, Index, CBO, etc.,• Handled files such as Avro, ORC, Parquet, JSON, XML, and CSV. • Consumed Data from Kafka using Spark Streaming Context as micro-batches to process it at the real-time/In-memory. • Hands-on experience in Function-Based model Spark, Python and Worked on Lamda Architecture.• Contributed to performance tuning, benchmarks, following best practices. • Used DevOps tools like Maven, Github, and JIRA. • Good working Experience in Spark core (RDD) and Spark SQL (Data frames and Datasets).• Working knowledge on Kafka messaging tool from source system by using NIFI push and pull the data from Spark Streaming. Good working Experience in loading data into Elastic search and visualization using Kibana.• Extensively worked on Oozie Workflow Engine to automate and parallelize Hadoop Sqoop, Hive, and Spark Jobs.• Good Experience in connection to any data source the Federated way in our Spark application.• Expertise in implement and design data solutions that use the following Azure services: Azure Cosmos DB, Azure Synapse Analytics, Azure Data Lake Storage, Azure Data Factory, Azure Stream Analytics, Azure Databricks, and Azure Blob storage.

Sep 2016 - Aug 2021

Consultant

Chennai, Tamil Nadu, India

Worked as Java Senior developer in Capgemini. I am a highly-skilled Java programmer with experience building web applications in Java ad its framework. I am responsible for analyzing user requirements and business objectives, determining application features and functionality, and recommending changes to existing Java-based applications, among other duties.As a Java Developer need to compile detailed technical documentation and user assistance material, requiring excellent written communication.

Jun 2013 - Sep 2016
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FAQ

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What company does Khader Basha work for?

Khader Basha works for Capgemini.

What is Khader Basha's role at Capgemini?

Khader Basha is listed as Technical Lead - Azure Data Engineering at Capgemini.

Where is Khader Basha based?

Khader Basha is based in Chennai, Tamil Nadu, India while working with Capgemini.

What companies has Khader Basha worked for?

Khader Basha has worked for Capgemini, Cognizant, and Infinite Computer Solutions.

Who are Khader Basha's colleagues at Capgemini?

Khader Basha's colleagues at Capgemini include Jabz J, Syed Nohid, Basant Singh, Shanthi Kumar Veparala, and Julian Toro.

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