Kartheek

adjljw@r.postjobfree.com

469-***-****

Summary: Data Analyst

Overall 7+ years of professional experience as a Software developer in design, development, deploying and supporting large scale distributed systems.

Around 6 years of extensive experience as a Data Engineer and Big data Developer specialized in Big Data Ecosystem-Data Ingestion, Modeling, Analysis, Integration, and Data Processing.

Extensive experience in providing solutions for Big Data using Hadoop, Spark, HDFS, Map Reduce, YARN, Kafka, Pig, Hive, Sqoop, HBase, Oozie, Zookeeper, Cloudera Manager, Horton works.

Strong experience working with Amazon cloud services like EMR, Redshift, DynamoDB, Lambda, Athena, Glue, S3, API Gateway, RDS, CloudWatch for efficient processing of Big Data.

Hands on experience building PySpark, Spark Java and Scala applications for batch and stream processing involving Transformations, Actions, Spark SQL queries on RDD’s, Data frames and Datasets.

Strong experience writing, troubleshooting and optimizing Spark scripts using Python, Scala.

Experienced in using Kafka as a distributed publisher-subscriber messaging system.

Strong knowledge on performance tuning of Hive queries and troubleshooting various issues related to Joins, memory exceptions in Hive.

Exceptionally good understanding of partitioning, bucketing concepts in Hive and designed both Managed and External tables in Hive.

Experience in importing and exporting data between HDFS and Relational Databases using Sqoop.

Experience in real time analytics with Spark Streaming, Kafka and implementation of batch processing using Hadoop, Map Reduce, Pig and Hive.

Experienced in building highly scalable Big-data solutions using NoSQL column-oriented databases like Cassandra, MongoDB and HBase by integrating them with Hadoop Cluster.

Extensive work on ETL processes consisting of data transformation, data sourcing, mapping, conversion and loading data from heterogeneous systems like flat files, Excel, Oracle, Teradata, MSSQL Server.

Experience of building ETL production pipelines using Informatica Power Center, SSIS, SSAS, SSRS.

Proficient at writing MapReduce jobs and UDF’s to gather, analyze, transform, and deliver the data as per business requirements and optimizing the existing algorithms for best results.

Experience in working with Data warehousing concepts like Star Schema, Snowflake Schema, DataMarts, Kimball Methodology used in Relational and Multidimensional data modeling.

Used AWS IAM, Kerberos and Ranger for security compliance.

Strong experience leveraging different file formats like Avro, ORC, Parquet, JSON and Flat files.

Sound knowledge on Normalization and De-normalization techniques on OLAP and OLTP systems.

Good experience with Version Control tools Bitbucket, GitHub, GIT.

Experience with Jira, Confluence and Rally for project management and Oozie, AirFlow scheduling tools.

Experienced in Strong scripting skills in Python, Scala and UNIX shell.

Involved in writing Python, Java API’s for Amazon Lambda functions to manage the AWS services.

Good Knowledge in building interactive dashboards, performing ad-hoc analysis, generating reports and visualizations using Tableau and PowerBI.

Experience in design, development and testing of Distributed Client/Server and Database applications using Java, Spring, Hibernate, Struts, JSP, JDBC, REST services on Apache Tomcat Servers.

Hands on working experience with RESTful API’s, API life cycle management and consuming RESTful services

Have good working experience in Agile/Scrum methodologies, communication with scrum calls for project analysis and development aspects.

Technical Skills:

Programming Languages: Python, Scala, SQL, Java, C/C++, Shell Scripting

Web Technologies: HTML, CSS, XML, AJAX, JSP, Servlets, JavaScript

Big Data Stack: Hadoop, Spark, MapReduce, Hive, Pig, Yarn, Sqoop, Flume, Oozie, Kafka, Impala, Storm

Amazon Web Services: S3, VPC, EC2, EMR, RedShift, DynamoDB, RDS, IAM, Lambda, API Gateway, Athena, Glue, CloudWatch, Kinesis

Relational databases: Oracle, MySQL, SQL Server, PostgreSQL, Teradata, Snowflake

NoSQL databases: MongoDB, Cassandra, HBase, Pig

Version Control Systems: Bitbucket, GIT, SVN, GitHub

Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Tweepy, Seaborn, TensorFlow, Keras, MLlib, Boto3

IDEs: PyCharm, Intellij IDEA, Jupyter Notebooks, Google Colab, Eclipse

Operating Systems: Unix, Linux, Windows

Professional experience:

Client: USAA July 2019 – present

Location: SanAntonio,TX

Role: Sr. AWS Data Engineer

Responsibilities:

Extensive experience in working with AWS cloud Platform (EC2, S3, EMR, Redshift, Lambda and Glue).

Working knowledge of Spark RDD, Data Frame API, Data set API, Data Source API, Spark SQL and Spark Streaming.

Developed Spark Applications by using Python and Implemented Apache Spark data processing Project to handle data from various RDBMS and Streaming sources.

Worked with the Spark for improving performance and optimization of the existing algorithms in Hadoop.

Using Spark Context, Spark-SQL, Spark MLlib, Data Frame, Pair RDD and Spark YARN.

Used Spark Streaming APIs to perform transformations and actions on the fly for building common.

Learner data model which gets the data from Kafka in real time and persist it to Cassandra.

Developed Kafka consumer API in python for consuming data from Kafka topics.

Consumed Extensible Markup Language (XML) messages using Kafka and processed the XML file using Spark Streaming to capture User Interface (UI) updates.

Developed Preprocessing job using Spark Data frames to flatten JSON documents to flat file.

Load D-Stream data into Spark RDD and do in memory data Computation to generate output response.

Experienced in writing live Real-time Processing and core jobs using Spark Streaming with Kafka as a Data pipeline system.

Migrated an existing on-premises application to AWS. Used AWS services like EC2 and S3 for data sets processing and storage.

Experienced in Maintaining the Hadoop cluster on AWS EMR.

Loaded data into S3 buckets using AWS Glue and PySpark. Involved in filtering data stored in S3 buckets using Elasticsearch and loaded data into Hive external tables.

Configured Snow pipe to pull the data from S3 buckets into Snowflakes table.

Stored incoming data in the Snowflakes staging area.

Created numerous ODI interfaces and load into Snowflake DB.

Worked on Amazon Redshift for shifting all Data warehouses into one Data warehouse.

Good understanding of Cassandra architecture, replication strategy, gossip, snitches etc.

Designed columnar families in Cassandra and Ingested data from RDBMS, performed data transformations, and then exported the transformed data to Cassandra as per the business requirement.

Used the Spark Data Cassandra Connector to load data to and from Cassandra.

Worked from Scratch in Configurations' of Kafka such as Mangers and Brokers.

Experienced in creating data-models for Clients transactional logs, analyzed the data from Cassandra.

Tables for quick searching, sorting and grouping using the Cassandra Query Language.

Tested the cluster performance using Cassandra-stress tool to measure and improve the Read/Writes.

Used Hive QL to analyze the partitioned and bucketed data, Executed Hive queries on Parquet tables.

Stored in Hive to perform data analysis to meet the business specification logic.

Used Apache Kafka to aggregate web log data from multiple servers and make them available in Downstream systems for Data analysis and engineering type of roles.

Worked in Implementing Kafka Security and Boosting its performance.

Experience in using Avro, Parquet, RCFile and JSON file formats, developed UDF in Hive.

Developed Custom UDF in Python and used UDFs for sorting and preparing the data.

Worked on Custom Loaders and Storage Classes in PIG to work on several data formats like JSON, XML, CSV and generated Bags for processing using pig etc.

Developed Sqoop and Kafka Jobs to load data from RDBMS, External Systems into HDFS and HIVE.

Developed Oozie coordinators to schedule Hive scripts to create Data pipelines.

Written several Map Reduce Jobs using Pyspark, Numpy and used Jenkins for Continuous integration.

Setting up and worked on Kerberos authentication principals to establish secure network communication.

On cluster and testing of HDFS, Hive, Pig and MapReduce to access cluster for new users.

Continuous monitoring and managing the Hadoop cluster through Cloudera Manager.

Environment: Spark, Spark-Streaming, Spark SQL, AWS EMR, map R, HDFS, Hive, Pig, Apache Kafka, Sqoop, Python, Pyspark, Shell scripting, Linux, MySQL Oracle Enterprise DB, SOLR, Jenkins, Eclipse, Oracle, Git, Oozie, Tableau, MySQL, Soap, Cassandra and Agile Methodologies.

Client: Medieval Times August 2018 – May 2019

Location: Dallas,TX

Role: Big Data / Hadoop Engineer

Responsibilities:

Worked as a Sr. Big Data/Hadoop Developer with Hadoop Ecosystems components like HBase, Sqoop, Zookeeper, Oozie, Hive and Pig with Cloudera Hadoop distribution.

Involved in Agile development methodology active member in scrum meetings.

Worked in Azure environment for development and deployment of Custom Hadoop Applications.

Designed and implemented scalable Cloud Data and Analytical architecture solutions for various public and private cloud platforms using Azure.

Involved in start to end process of Hadoop jobs that used various technologies such as Sqoop,PIG, Hive, MapReduce, Spark, and Shells scripts.

Implemented various Azure platforms such as Azure SQL Database, Azure SQL Data Warehouse, Azure Analysis Services, HDInsight, Azure Data Lake and Data Factory.

Extracted and loaded data into Data Lake environment (MS Azure) by using Sqoop which was accessed by business users.

Manage and support of enterprise Data Warehouse operation, big data advanced predictive application development using Cloudera & Hortonworks HDP.

Developed PIGscripts to transform the raw data into intelligent data as specified by business users.

Utilized Apache Spark with Python to develop and execute Big Data Analytics and Machine learning applications, executed machine learning use cases under Spark ML and MLLib.

Installed Hadoop, Map Reduce, HDFS, Azure to develop multiple MapReduce jobs in PIG and Hive for data cleansing and pre-processing.

Used SparkAPI over HortonworksHadoopYARN to perform analytics on data in Hive.

Improved the performance and optimization of the existing algorithms in Hadoop using SparkContext, Spark-SQL, Data Frame, Pair RDD's, Spark YARN.

Developed Spark code using Scala and Spark-SQL/Streaming for faster testing and processing of data.

Developed a Spark job in Java which indexes data into Elastic Search from external Hive tables which are in HDFS.

Performed transformations, cleaning and filtering on imported data using Hive, MapReduce, and loaded final data into HDFS.

Explored with the Spark improving the performance and optimization of the existing algorithms in Hadoop using Spark Context, Spark-SQL, Data Frame, Pair RDD's, Spark YARN.

Import the data from different sources like HDFS/HBase into Spark RDD and developed a data pipeline using Kafka and Storm to store data into HDFS.

Used Spark streaming to receive real time data from the Kafka and store the stream data to HDFS using Scala and NoSQLdatabases such as HBase and Cassandra.

Documented the requirements including the available code which should be implemented using Spark, Hive, HDFS, HBase and Elastic Search.

Performed transformations like event joins, filter boot traffic and some pre-aggregations using Pig.

Explored MLLibalgorithms in Spark to understand the possible Machine Learning functionalities that can be used for our use case

Used windows Azure SQL reporting services to create reports with tables, charts, and maps.

Executed Hive queries on Parquet tables stored in Hive to perform data analysis to meet the business requirements.

Configured Oozie workflow to run multiple Hive and Pig jobs which run independently with time and data availability.

Imported and exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports for the BI team.

Environment: Hadoop 3.0, Azure, Sqoop 1.4.6, PIG 0.17, Hive 2.3, MapReduce, Spark 2.2.1, Shells scripts, SQL, Hortonworks, Python, MLLib, HDFS, YARN, Java, Kafka 1.0, Cassandra 3.11, Oozie, Agile

Client: Wintrust Financial Corp July 2016 – Aug 2018

Location: Rosemont, IL

Role: Big Data Engineer

Responsibilities:

Imported the data from various formats like JSON, Sequential, Text, CSV, AVRO and Parquet to HDFS cluster with compressed for optimization.

Worked on ingesting data from RDBMS sources like - Oracle, SQL Server and Teradata into HDFS using Sqoop.

Loaded all datasets into Hive from Source CSV files using Spark and Cassandra from Source CSV files using Spark

Created environment to access Loaded Data via Spark SQL, through JDBC&ODBC (via Spark Thrift Server).

Developed real time data ingestion/ analysis using Kafka / Spark-streaming.

Configured Hive and written Hive UDF's and UDAF's Also, created Static and Dynamic with bucketing as required.

Worked on writing Scala programs using Spark on Yarn for analyzing data.

Managing and scheduling Jobs on a Hadoop cluster using Oozie.

Created Hive External tables and loaded the data into tables and query data using HQL.

Written Hive jobs to parse the logs and structure them in tabular format to facilitate effective querying on the log data.

Developed Oozie workflow for scheduling and orchestrating the ETL process and worked on Oozie workflow engine for job scheduling.

Managed and reviewed the Hadoop log files using Shell scripts.

Migrated ETL jobs to Pig scripts to do transformations, even joins and some pre-aggregations before storing the data onto HDFS.

Using Hive join queries to join multiple tables of a source system and load them to Elastic search tables.

Real time streaming, performing transformations on the data using Kafka and Kafka Streams.

Built NiFidataflow to consume data from Kafka, make transformations on data, place in HDFS & exposed port to run Spark streaming job.

Developed Spark Streaming Jobs in Scala to consume data from Kafkatopics, made transformations on data and inserted to HBase.

Implemented Spark using Scala and SparkSQL for faster testing and processing of data.

Experience in managing and reviewing huge Hadoop log files.

Collected the logs data from web servers and integrated in to HDFS using Flume.

Expertise in designing and creating various analytical reports and Automated Dashboards to help users to identify critical KPIs and facilitate strategic planning in the organization.

Involved in Cluster maintenance, Cluster Monitoring and Troubleshooting.

Migrated the computational code in HQL to PySpark.

Completed data extraction, aggregation and analysis in HDFS by using PySpark and store the data needed to Hive.

Developed Python code to gather the data from HBase (Cornerstone) and designs the solution to implement using PySpark.

Maintaining technical documentation for each and every step of development environment and launching Hadoop clusters.

Worked on different file formats like Parquette, Orc, Avro, Sequence files using MapReduce/Hive/Impala.

Worked with Avro Data Serialization system to work with JSON data formats.

Used Amazon Web Services (AWS) S3 to store large amount of data in identical/similar repository.

Worked with the Data Science team to gather requirements for various data mining projects.

Automated the process of rolling day-to-day reporting by writingshell scripts.

Involved in build applications using Maven and integrated with Continuous Integration servers like Jenkins to build jobs.

Worked on BI tools as Tableau to create dashboards like weekly, monthly, daily reports using tableau desktop and publish them to HDFS cluster.

Environment: Spark, Spark SQL, Spark Streaming, Scala, Kafka, Hadoop, HDFS, Hive, Oozie, Pig, Nifi, Sqoop, AWS (EC2, S3, EMR), Shell Scripting, HBase, Jenkins, Tableau, Oracle, MySQL, Teradata and AWS.

Client: Data metica Solutions June 2013 – May 2015

Location: India

Role: Data Analyst

Responsible for gathering requirements from Business Analyst and Operational Analyst and identifying the data sources required for the request.

Created value from data and drive data-driven decisionsby performing advanced analytics and statistical techniques to determine to deepen insights, optimal solution architecture, efficiency, maintainability, and scalability which make predictions and generate recommendations.

Enhancing data collection procedures to include information that is relevant for building analytic systems.

Worked closely with a data architect to review all the conceptual, logical and physical database design models with respect to functions, definition, maintenance review and support data analysis, Data quality and ETL design that feeds the logical data models.

Maintained and developed complex SQL queries, stored procedures, views, functions, and reports that qualify customer requirements using SQL Server 2012.

Creating automated anomaly detection systems and constant tracking of its performance.

Support Sales and Engagement's management planning and decision making on sales incentives.

Used statistical analysis, simulations,predictive modelling to analyze information and develop practical solutions to business problems.

Extending the company's data with third-party sources of information when needed.

Précised development of several types of sub-reports, drill down reports, summary reports, parameterized reports, and ad-hoc reports using SSRS through mailing server subscriptions &SharePoint server.

Generated ad-hoc reports using Crystal Reports 9 and SQL Server Reporting Services (SSRS).

Developed the reports and visualizations based on the insights mainly using Tableau and dashboards for the company insight teams.

Environment: SQL Server 2012, SSRS, SSIS, SQL Profiler, Tableau, Qlik View, Agile, ETL, Anomaly detection.

Client: Sutherland June 2012 – May 2013

Location: India

Role: Research Analyst

Responsibilities:

Programming socio-economic experiments in ztree (C++); creating and analyzing surveys in Behavery, Qualtrics and responsible for spot modifications and on-call debugging.

Maintain the subject pool database (hroot and MySQL), troubleshooting the lab server (Linux and Ruby-on-Rails).

Automated several manual data reports in MS Excel using Macros, VBA and reduced turn-around times for reporting from days to minutes.

Demonstrated abilities to extract, transform, load (ETL) operational data using SQL queries shortening the average processing time by 10 minutes.

Created financial reports and dashboards using Tableau by using advance functionalities such as animations, interactive charts etc. Accomplished data collecting, cleansing, data modelling, data profiling, data queries to analyze the data from different sources.

Performed exploratory and descriptive data analysis using MS Excel (Pivot tables, formulas, functions) and reported to the senior management team.

Involved in addressing a wide range of challenging problems using techniques from applied statistics, machine learning and data mining fields. Explored and analyzed the customer specific features by using Matplotlib, Seaborn in Python and implemented dashboards in Tableau.

Speaker at “Essex Summer School 2016 in Social Science Data Analytics” on zTree Programming, A/B Testing and Survey Analytics.

Environment: zTree, C++, MySQL, Linux, MS Excel, Macros, VBA, Tableau, Qualtrics, SurveyMonkey, Behavery, Statistics.

Education:

Electronics and Communications Engineering – Vellore Institute of Technology (VIT).

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