Kwajabhai Maktedar — Lead ML Engineer

Roles Played : Azure Solution Architect, Data Science Architect, Lead Data Engineer, Data Scientist. Deep learning engineer, ML engineer , Senior Data Engineer, Data Engineer, Data Warehouse Engineer & ETL Developer. ⦁ Designed Data warehouse, Data lake, Data Mesh Architecture in Azure, AWS and GCP . ⦁ Designed Predictive Pricing, Spare parts recognition, PowerBI Search Quality Engine. Language translator model. ⦁ Azure - Microsoft Azure, Azure Data Factory V1 & V2, Azure Databricks, Azure SQL Database, Azure Synapse Analytics, Azure Data lake, Azure DevOps, EventHub, Service Bus, IOT hub ,Azure Storage gen1 & 2,Azure Purview, Unity Catalog, Azure monitor & Key vault ⦁ Big Data – Hadoop 1.x & 2.x .Hive, Pig, HBase, Impala, ,Sqoop, Zoo Keeper, Airflow, Nifi ,Kafka, Flume ⦁ Language – Python 3.x & 2.7 , U-SQL, SQL, HQL, Scala 2.11.12 & R ⦁ Framework - Spark, Hadoop ⦁ Scripting Language – PowerShell, Shell. ⦁ TimeSeries Databases: Influx DB, Timescale DB, Azure Data explorer and ClickHouse. ⦁ RDMS Database – MySQL Oracle & SQL server. ⦁ NoSQL Database- Cassandra, Cosmos DB, HBase, Mongodb. ⦁ Cache Database – Reddis. ⦁ ETL Tools: SSIS, Azure data factory, Azure data factory v2, Pentaho & Talend. ⦁ Reporting Tool – Grafana & PowerBI ⦁ Cloud Platform - Microsoft Azure, Google Cloud Platform & AWS ⦁ Data Science/Machine learning : Descriptive Statistics, Inferential Statistics, EDA, Dimensionality Reduction ,Feature Engineering Machine Learning ,Predictive Modeling ,Data Mining, Cluster Analysis, Text Mining & Image Processing, Neural Network, Linear Algebra ⦁ Designed and implemented statistical / predictive models, data mining techniques like clustering, linear regression, logistic regression, decision tree, demand forecasting, Time series algorithms etc.. ⦁ Worked as scrum master by leading various project groups to achieve specific project milestones and deliverables by interacting with Stake holders & Product Owners.

Stackforce AI infers this person is a Data Engineering and Data Science expert with strong cloud architecture skills.

Location: Bengaluru, Karnataka, India

Experience: 12 yrs 10 mos

Skills

Data Science
Machine Learning
Big Data
Data Engineering

Career Highlights

Expert in Azure and AWS cloud architectures.
Proficient in data science and machine learning techniques.
Led multiple successful data engineering projects.

Work Experience

Fractal

Lead Data Architect (1 yr 3 mos)

LTI - Larsen & Toubro Infotech

Senior specialist-Data Engineering (3 yrs 8 mos)

Microsoft

Senior Data Specialist (2 yrs 11 mos)

Sears Holdings Corporation

Associate Data Scientist (1 yr)

Mindtree

Senior Data analyst (3 yrs 11 mos)

Education

B.E at BASAVESHWAR ENGINEERING COLLEGE,BAGALKOT

Kwajabhai Maktedar

Lead ML Engineer

Bengaluru, Karnataka, India12 yrs 10 mos experience

Highly Stable

Key Highlights

Expert in Azure and AWS cloud architectures.
Proficient in data science and machine learning techniques.
Led multiple successful data engineering projects.

Stackforce AI infers this person is a Data Engineering and Data Science expert with strong cloud architecture skills.

Contact

kwajabhai.mktdr@gmail.com +916362599807 LinkedIn

Skills

Core Skills

Data ScienceMachine LearningBig DataData Engineering

Other Skills

Amazon Web Services (AWS)Analytical SkillsApache PigApache SparkAzure DatabricksBig data conceptsCassandraClusteringData WarehousingData analysisData mining techniquesHadoopHiveLinuxLogistic regression

About

Experience

Fractal

Lead Data Architect

Dec 2024 – Present · 1 yr 3 mos

Lti - larsen & toubro infotech

Senior specialist-Data Engineering

Apr 2021 – Dec 2024 · 3 yrs 8 mos

Microsoft

Senior Data Specialist

Apr 2018 – Mar 2021 · 2 yrs 11 mos · Hyderabad Area, India

Sears holdings corporation

Associate Data Scientist

Mar 2017 – Mar 2018 · 1 yr · Bengaluru Area, India

Worked on data mining techniques like clustering, multiple linear regression, and logistic regression.
Experience in Text analytics techniques .
Worked on Spark (Spark SQL, data frame and RDD) and understanding of big data concept.
Designed and implemented statistical / predictive models, data mining techniques like clustering, linear regression, logistic regression, decision tree, demand forecasting, Time series algorithms etc..

Data mining techniquesClusteringMultiple linear regressionLogistic regressionSparkBig data concepts+3

Mindtree

Senior Data analyst

Mar 2013 – Feb 2017 · 3 yrs 11 mos · Bengaluru Area, India

Spark Developer.
Written a spark jobs in Scala using Spark SQL(Datasets,Dataframe)
Build a Recommendation model in SparkML for one of the World largest retail firm.
Build a classification algorithm using k-means in SparkML.
Build a pattern matching algorithm in Spark-ML.
Migrated a complete Recommendation model projects from RDBMS(SQL-server SP's) to Spark.
Done optimization of spark jobs.
Worked on spark version 2.X.
Hadoop Developer.
Developed Hive scripts for end user / analyst requirements for Ad hoc analysis.
Used and Wrote Partitions, Bucketing concepts in Hive and designed both Managed and External
tables in Hive for optimized performance.
Solved performance issues in Hive and Pig scripts with understanding of Joins, Group and
aggregation and how does it translate to MapReduce jobs.
Used Sqoop in performing last modified and append imports from MySQL to HDFS.
Wrote Hive queries for data analysis to meet the business requirements.
Worked on analyzing Hadoop cluster using different big data analytic tools including Pig, Hive, and MapReduce.
Collecting and aggregating large amounts of log data using Apache Flume and staging data in HDFS for further analysis
Worked on debugging, performance tuning of Hive & Pig Jobs.
Implemented test scripts to support test driven development and continuous integration.
Worked on tuning the performance Map-Reduce jobs.
Involved in loading data from LINUX file system to HDFS.
Importing and exporting data into HDFS and Hive using Sqoop.
Experience working on processing unstructured data using Pig and Hive.
R Programming.
Worked on data mining techniques like clustering, multiple linear regression, logistic regression, decision tree, demand forecasting etc.
Experience on Text analytics techniques (sentiment analysis, word cloud, topic modelling)
Strong work Experience on Data analysis, exploratory data analysis.