Jayaseelan Joseph
Chennai
Summary
Having almost 7 years of experience in designing and developing Big Data applications using the Hadoop Ecosystem technologies (HDFS, Hive, Sqoop, Apache Spark and AWS). Experienced in optimizing Spark RDD performance by fine-tuning various configuration settings, including memory allocation, caching strategies, and serialization methods.
Overview
7
7
years of professional experience
Work History
Data Engineer
Capgemini Technology Services
Chennai
04.2022 - 07.2024
- Implemented Spark transformations to process large-scale healthcare data for analysis
- Deployed Spark applications in a distributed environment using YARN or Kubernetes
- Managed Spark libraries and dependencies
- Worked with Spark DataFrame APIs for structured data analysis
- Implemented data validation and quality checks within Spark transformations
- Integrated Spark with AWS Lambda for server less data processing solutions
- Skilled in integrating Hive tables with other big data technologies, such as Hadoop, HBase, and Impala
- Familiarity with Hive metastore and its role in managing table metadata and schema evolution
- Proficient in optimizing Hive query performance by tuning various configuration settings, such as memory allocation, parallelism, and compression
- Strong understanding of Hive integration with other big data technologies, such as Hadoop, Spark, and Impala, and their impact on query performance and resource utilization
- Proficient in performing data validation and cleansing during data transfer using Sqoop's validation and cleansing options
- Adept in scheduling and automating Sqoop jobs for incremental runs
- Experienced in importing and exporting large datasets between Hadoop and relational databases using Sqoop
- Proficient in writing Sqoop commands to transfer data between Hadoop and various databases such as MySQL, and SQL Server
- Skilled in implementing Sqoop-based solutions for migrating data between different Hadoop distributions and versions
- Strong experience in configuring Sqoop to handle complex data structures such as nested and hierarchical data
ETL Developer
Maersk Global service
Chennai
10.2017 - 04.2022
- Experienced in ETL (Extract, Transform, Load) testing methodologies and processes
- Proficient in testing data extraction processes from various sources, including databases, files, and APIs
- Knowledgeable about data integration and consolidation processes in ETL pipelines
- Familiarity with data quality and data cleansing techniques in ETL testing
- Expertise in testing ETL workflows and job scheduling mechanisms
- Expertise in testing ETL transformations, such as data aggregation, filtering, sorting, and joining
- Knowledgeable about testing ETL processes in Big Data platforms, such as Hadoop or Spark
- Experienced in conducting data validation and reconciliation between source and target systems in ETL testing
- Strong understanding of data deduplication and data consolidation techniques in ETL testing
- Expertise in testing data transformation rules and business logic applied during ETL processes
- Proficient in using ETL testing tools and frameworks, such as QuerySurge, Talend Data Quality, or Informatica Data Validation Option
Education
Bachelor of Commerce -
Loyola College
03.2017
Skills
- Apache Spark
- Sqoop
- Hadoop
- Hive
- Scala, Data Warehouse
- Big query
- Putty
- AWS S3
Professional Summary
● Experienced in optimizing Spark RDD performance by fine-tuning various configuration settings, including memory allocation, caching strategies, and serialization methods.
● Expertise in using Spark RDD transformations and actions to process large-scale structured and unstructured data sets, including filtering, mapping, reducing, grouping, and aggregating data.
● Skilled in using Spark RDD persistency and caching mechanisms to reduce data processing overhead and improve query performance.
● Familiar with schema and data type operations, such as adding, renaming, and dropping columns, casting data types, and handling null values.
● Skilled in optimizing Spark SQL performance through memory allocation, caching, and serialization.
● Proficient in processing serialized data using Avro, Parquet, ORC, and Protobuf.
● Experienced with binary and textual data formats, such as CSV, JSON, and XML, including serialization and deserialization using Spark DataFrames and RDDs.
● Optimized Spark jobs and data workflows for scalability, performance, and cost efficiency using partitioning, compression, and caching.
● Performed data cleansing and preprocessing using Spark transformations.
● Implemented Spark SQL queries for data querying and aggregation.
● Proficient in setting up and customizing Google Dataproc clusters, including cluster resizing and configuration tuning.
● Experienced in ETL testing methodologies, including data extraction from various sources, workflow testing, job scheduling, and transformation testing.
● Executed data cleansing and preprocessing tasks using Spark transformations to prepare data for analysis and reporting.
Personal Information
- Date of Birth : 16/11/1995
- Gender : Male
- Nationality : Indian
- Marital Status : Married
- Father's Name : A . Joseph
Timeline
Data Engineer
Capgemini Technology Services
04.2022 - 07.2024
ETL Developer
Maersk Global service
10.2017 - 04.2022
Bachelor of Commerce -
Loyola College
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