Python Developer / Data Engineer Resume Mount Laurel, NJ - Hire IT People

SOFTWARE/SKILLS:

Python 2.7 - 3.6 (pandas, numpy, pymysql, pymongo, flask, asyncio, aiomysql, uvloop, concurrent.futures, requests, beautifulsoup, among other libraries)
MySQL, MemSQL, SQL Server, MongoDB, JSON
RabbitMQ, Kafka, Celery
Sentry, Grafana, Kibana
HTML, CSS, jQuery, Vanilla Javascript
Linux, Git
Adobe Illustrator & Adobe Photoshop CS6
ArcGIS 10.4+ (Spatial Analyst, Network Analyst, Production Mapping, Defense Mapping)
Microsoft Office Suite

EMPLOYMENT EXPERIENCE:

Confidential

Python Developer / Data Engineer, Mount Laurel, NJ

Responsibilities:

Developed efficient ETL processes using python with libraries like pandas and numpy.
Created a highly scalable python job scheduling tool complete with a web interface for managing ETL jobs and tracking information about the jobs. The tool was developed using a flask and jinja2 backend as a RESTful API, and the front end was developed using HTML, CSS and jQuery. The scheduler used RabbitMQ as the messaging broker to schedule jobs that would be picked up by a cluster of workers that would track information about jobs as they ran and report the information back to the web interface.
Built and designed a distributed data pipeline with Python, RabbitMQ, and Celery that logged into and ingested millions of records of data from a CMTS daily. This became the main data warehouse for all CMTS data across the Confidential network.
Developed a data integrity tool with python and flask that periodically checks SQL and NoSQL databases to ensure data is being populated accurately by ETL processes.
Regularly created and performed queries on MySQL, MemSQL, SQL Server and NoSQL databases like MongoDB.
Worked on Linux systems in a cloud environment to create highly scalable efficient data solutions.

Confidential

GIS Technician, Mount Laurel, NJ

Responsibilities:

Developed highly efficient geospatial tools written in python using arcpy to automate tasks such as attribution updates and conflation of points, lines and polygons.
Digitized maps of the world over satellite imagery complete with attribution.
Conflated large scale geospatial datasets into one using tools built by myself in python and quality checked the accuracy.
Used 3D satellite imagery to get elevation data to create accurate maps.