Cloud Data Engineer Resume

SUMMARY

IT professional having more TEMPthan 7 years of experience in teh domains of Banking, Healthcare, Health & Welfare Benefits and Lifesciences wif solid coding skills, data engineering and machine learning knowledge.
Proficient in Python, AWS and DevOps to handle complex use cases. Exposure to SDLC and agile methodologies. Resourceful, detail oriented, collaborative and results driven.

PROFESSIONAL EXPERIENCE

Cloud Data Engineer

Confidential

Responsibilities:

Created Python scripts to automate teh process of downloading files from S3 bucket, decrypting them & feeding it to a third - party application N-Tier, pushing teh output files of N-Tier to a regulatory service Finra and pulling teh feedback, error files, reference data files from Sftp & URLs
Deployed scripts, application, python packages using Ansible and source code control using Bit Bucket
Automation using Boto3 SDK to archive and retrieve files from S3 Glacier
Leveraged cloud formation templates for AWS Parameter Store Integration for storing variables and AWS Event Bridge for scheduling jobs to trigger scripts in EC2 instances
Used AWS Secrets Manager for securing credentials and lambda function for triggering scripts from EC2 instances
Queried teh tables created from AWS Glue Data catalog using Atana wif S3 as data store
Leveraged AWS Cloud9 to for creating python scripts and commit teh code changes to code build repository and trigger teh code pipeline
Monitored job status using cloud watch metrics AWS Run command history in Systems Manager

Data Engineer

Fidelity Investments

Responsibilities:

Migrated on-prem oracle database to oracle RDS in AWS for a banking project
Created python scripts for automation of database migration using concourse pipelines
Prepared pipeline yaml files and cloud formation json files and used git to push files into bit bucket
Created concourse pipeline and built docker images from an existing image
Validated database migration end to end using Unix and sqlplus on Linux servers
Performed Oracle database export and import using command-line clients, Data Pump API and Metadata API
Worked on machine and deep learning models such as Spacy, Bi-Lstm, Spark NLP using Python and PySpark to create digital encyclopedia of Indianapolis
Built machine learning and deep learning models to extract causal effect relationship in diseases
Created a dashboard for Informatics department project management, using Tableau to make key funding decisions
Analyzed, validated, and cleaned data using excel, data modeling using MySQL and data mining using complex SQL queries

Data Analyst

Confidential

Responsibilities:

Analyzed, transformed, and Integrated huge data sets using Excel & Oracle for Health Benefits Administration projects in teh operations domain
Presented monthly Tableau reports to executives emphasizing business process improvement and achieved 20% reduction in customer service calls received over teh duration of 2 months
Worked directly wif clients and vendors to translate between data and business needs. Collaborated wif cross-functional teams, handled multiple concurrent projects, and managed a team of 4.
Created source to target mapping documents and end-to-end ETL process from source systems to staging area, to data warehouse for a pharmaceutical client master data management
Implemented complex business rules by creating re-usable transformations, mappings, mapplets, exception handling process and address doctor package in Informatica data quality
Loaded fact, dimension tables by creating jobs in Informatica power center and executed testing using Oracle and achieved 85% improvement in data quality
ETL Tester for teh project aimed at building an enterprise data warehouse for a healthcare payer insurance client
Prepared Interface estimates, test cases, scripts, plan, release notes for multiple interfaces - Provider, Member, Claims, Groups
Scripted complex SQL queries like walking teh tree rule, SCD and validated healthcare data & Business Object reports
Analyzed defects, created periodic defect status reports using Application life cycle management, performed root cause analysis, and minimized defects by 15%

TECHNICAL SKILLS

AWS: Glue, Atana, EMR, EC2, S3, Glacier, Parameter Store, Secrets Manager, Event Bridge, Lambda, SNS, CloudWatch, CloudFormation, RDS, Cloud9, CodePipeline, CodeBuild, CodeCommit

Programming Languages: Python, PySpark, Unix

CI/CD Tools: Git, Ansible

Data Visualization: Tableau, Matplotlib, Seaborn

Databases: Oracle, MS SQL Server, My SQL

ETL Tools: Informatica PowerCenter, Informatica Data Quality

Defect Management Tools: HP Quality Control, Application Lifecycle Management

Machine Learning: Supervised learning and Unsupervised learning

Deep Learning: CNN, RNN, LSTM, Bi-LSTM, NLP - NLTK, Spacy

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