Narendra Reddy Yediginjala
Verified Expert in Engineering
Big Data Developer
Bengaluru, Karnataka, India
Toptal member since April 9, 2020
Narendra has 18 years of experience in data engineering, data science, business intelligence, and data warehousing. He has handled multimillion-dollar projects for clients and worked with numerous big data tools, including Databricks, AWS, Google Cloud, Hadoop, Hive, Spark, Scala, Python, and SQL. Narendra's most significant projects have been for financial services and healthcare clients, including HelloFresh, Change Healthcare, Aetna, TIAA-CREF, and ADP.
Portfolio
Experience
- SQL - 14 years
- IBM InfoSphere (DataStage) - 9 years
- Apache Hive - 5 years
- Hadoop - 5 years
- Big Data - 5 years
- Spark - 4 years
- Amazon Elastic MapReduce (EMR) - 1 year
- Amazon S3 (AWS S3) - 1 year
Work Experience
Senior Big Data Engineer
Change Healthcare
- Created Spark programs with Scala to generate demographic relative scores based on different algorithms.
- Developed and enhanced a demographics-based identity platform.
- Created, administered, and managed EMR clusters on an AWS platform to run the Sparks program.
- Worked extensively on AWS S3, AWS Glue, and EMR for data processing.
- Extracted data from sources using Fivetran and dbt tools.
- Wrote data lake pipelines using tools like dbt, AWS, and Airflow.
Senior Associate
Cognizant Technology Solutions US Corp
- Worked on multiple multimillion-dollar projects with different clients.
- Migrated a slow-performing data reporting platform to distribute a computing-based data platform using Oracle BDA.
- Enhanced and maintained TIAA PlanFocus, an application for a data reporting platform.
- Worked on a data integration platform to gather, transform, and report data from multiple sources.
- Rewrote ETL jobs from Talend to IBM DataStage with enhanced reusability and performance.
- Migrated a reporting platform from T+2 ETA to T+1 8 AM ETA.
Technology Lead
Infosys Limited
- Rewrote and enhanced the functionalities for a new business-related reporting system.
- Modified parallel jobs to include recent changes, migrating the old data from DB2 history tables to Oracle tables.
- Developed data model changes for the functional enhancements to coordinate with the DBA team to get the necessary requirements.
- Migrated from a legacy platform to a modern eCommerce platform with minimal issues.
- Kept pace with the frequently changing user requirements and delivered high-quality parallel jobs on time.
Senior Member–Technical
ADP Private Limited
- Developed ETL jobs using data rules defined by the business.
- Wrote and executed unit test scripts using internally developed frameworks.
- Supported ETL jobs in the production environment and resolved issues as they arose.
Project History
UPI – IHDP
JAD (Joint Application Development) – Data Science
Finance Data Repository (FDR)
Consultant Book of Business (CBOB)
PlanFocus T1
TIAA-CREF has invested in PlanFocus to improve its functionalities and services. PlanFocus T1 is a project to improve data availability for plan sponsors. Before this project, data was refreshed within two days. This project aimed to provide data to plan sponsors within one day by 8:00 AM.
PlanFocus Data Integration
The platform consists of several self-service tools that gather many data attributes from multiple systems and databases. The data integration system collects data from discrete systems; cleanses, analyzes, and transforms it; and sends report-ready data to a memory-stored data presentation system (Endeca) that creates PlanFocus reports.
I executed multiple functional enhancements and InfoSphere server upgrades.
Education
Executive MBA in Management
Quantic School Of Technology and Management - Washington, D.C., USA
Bachelor of Technology Degree in Electrical and Electronics Engineering
Jawaharlal Nehru Technological University - Hyderabad, India
Certifications
Google Cloud Platform Big Data and Machine Learning Fundamentals
Coursera
Smart Analytics, Machine Learning, and AI on GCP
Coursera
Modernizing Data Lakes and Data Warehouses with GCP
Coursera
Building Resilient Streaming Analytics Systems on GCP
Coursera
Building Batch Data Pipelines on GCP
Coursera
CCA Spark and Hadoop Developer
Cloudera
Problem Solving (Basic)
HackerRank
Python (Basic)
HackerRank
Machine Learning
Coursera
Machine Learning
Coursera
Skills
Libraries/APIs
PySpark, Pandas, NumPy
Tools
IBM InfoSphere (DataStage), Impala, BigQuery, Amazon QuickSight, IntelliJ IDEA, Cloudera, Hue, Amazon Elastic MapReduce (EMR), Spark SQL, Google Sheets, Stitch Data, Geocoding, Microsoft Power BI
Languages
SQL, Python 3, Python, Scala, Bash, Stored Procedure, Snowflake
Frameworks
Hadoop, Spark
Paradigms
ETL, Dimensional Modeling, MapReduce, Agile Software Development, Management
Platforms
Oracle, Amazon Web Services (AWS), Linux, Azure, Spark Core, Google Cloud Platform (GCP), Databricks
Storage
Apache Hive, Amazon S3 (AWS S3), Databases, Google Cloud, PL/SQL, HDFS, Datastage, IBM Db2, MySQL, Distributed Databases, Data Pipelines, Data Lakes
Other
Data Warehousing, Data Warehouse Design, Big Data, Data Engineering, Data Modeling, Data Marts, ELT, Fivetran, EMR, Engineering, Development, Data Science, Machine Learning, Data, Team Leadership, Cloud Infrastructure, Marketing Analytics, Streaming Data, Cloud Architecture, Data Build Tool (dbt), Data Architecture, Data Visualization, Electronic Medical Records (EMR), Strategy, Accounts
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