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Python Consultant← All Jobs

2019-07-12 | Chicago IL | DOE | 12 Months+ Contract


Description

Python Data Engineering
Chicago, IL
Long Term Contract

Technical/Functional Skill:
• Good Understanding of various Python libraries like NumPy, SciPy, Panda etc.
• Hands on experience on Google Cloud and big query
• Strong object oriented programming experience to include backend APIs, web-services
• Experience writing scripts using PowerShell, Putty...etc for Applications automation.
• Experience with SQL and NoSQL databases.
• Experience with any major cloud provider, cloud automation and cloud native database technologies
• Infrastructure as code experience using CloudFormation, Terraform etc.
• Good understanding using developer tools, including CI/CD pipelines. Designing and operating CI/CD pipelines for database automation is an advantage.

Experience Required:
• Hands on experience in core Python programming language
• Experience with Extract, Transform, and Load (ETL) processes, including document parsing techniques and managing large data sets, including multi TB scale
• Experience with multi–threaded, Big Data, and distributive Cloud architectures and frameworks, including Hadoop, Hive, Spark for Big Data analytics
• Knowledge of Web services environments, languages, and formats, including RESTful APIs, HTML, JavaScript, XML, KML, SOAP, or JSON
• Extensive knowledge Python Data manipulation libraries (Pandas, numpy, petl etc)
• Relational databases (MySQL, Postgres, Oracle, etc.)
• Data harmonization and ETL processes
• Excellent knowledge of data modeling
• Git, GitHub pull requests, and continuous integration
• Experience in eCommerce.

s & Responsibilities:
• Designing and analyzing tasks and programs to measure the impact of product features and make calculated modifications based on desired results
• Analyze and resolve complex problems associated with applications systems
• Detect, diagnose and report related problems
• Creating metrics and aggregations in the data collections to define new qualitative and quantitative questions as ed by the audience and performance teams
• Building dashboards and models to predict the growth trajectory of segments
• Collaborate on best practices, code reviews, internal tools and process improvement


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