Responsible for unit test and developing enhancements for the applications “AURA Playground” and “AURA Service Client”.

• Developed a Service Client library for AURA with functionalities such as:

1. 1. Data Services: class that includes methods status (checks for AURA's webservices) and methodology (performs a partial and full rebalance, using **kwargsin order to pass as many items as needed to build the URL)

   2. Function Services: class that includes method perform_rebalance (performs partial and full with prepared data, using **kwargsin order to pass as many items as needed to build the URL)

• Developed an Enum file that contains the valid URLs to be requested whenever any of the functionalities were being used.

• Created unit test for each functionality in the Service Client library.

• Developed Median function for AURA, which calculates the median in a column of numerical values by using Numpy and Pandas, of the value in a new user-defined column, unit test included.

• Developed Rank function for AURA, which evaluates each value in a column of numerical values and returns the relative standing, in a specified order using Numpy and Pandas, of the value in a new user-defined column, unit test included.

• Developed RankByGroup function for AURA, which groups values together by a column specified in Parameters, and then evaluates each value in a column of numerical values and returns the relative standing within each group, in a specified order using Numpy and Pandas, of that value in a new user-defined column, unit test included.

• Developed Average function for AURA, which averages a column of numerical values by using Numpy and Pandas, in a new user-defined column, unit test included.

• Developed Max function for AURA, which calculates the maximum value of a column of numerical values by using Numpy and Pandas, in a new user-defined column, unit test included.

• Developed Min function for AURA, which calculates the minimum value of a column of numerical values by using Numpy and Pandas, in a new user-defined column, unit test included.

• Developed Segment function for AURA, which extracts segments from a string of a column of alphanumerical values by using Numpy and Pandas, in a new user-defined column, unit test included.

• Developed Absolute function for AURA, which calculates the absolute value of a column of numerical values by using Numpy and Pandas, in a new user-defined column, unit test included.

Responsible for Unit and UI Regression Tests for “MultiBasket” and “ETF Multi Basket Submission” API’s, as well as giving maintenance & support, and developing enhancements for the API’s.

Responsible for planning the architect for “Support Tool” API in order to retrieve every dependency related to a specific API that is being monitored and display it as a knowledge graph, as well as developing functionalities along with Unit Tests.

• Coordinated with team members to develop “Support Tool” API architect.

• Analyzed and gathered the key attributes for the “Support Tool” API configuration file in order to create the main architect for each section (ETF, Price Source, Source).

• Designed the store architect for the dependencies of each ETF, where it contains which company and price source is related to it as well as what kind of node type it belonged to (ETF in this case).

• Designed the store architect for the dependencies of each Source, where it contains the companies that were involved in each source as well as the dependencies for each one of them such as the credentials, db config name, db name, file region, file type, host, port, table name, and finally what kind of node was it (Source in this case).

• Designed the store architect for the dependencies of each Price Source, where it contains the bondset, container, day, db table, host, identifier, path, port, region, snap time, and finally what kind of node was it (Price Source in this case).

• Build queries in SQL to retrieve information from SANDRA in order to evaluate ETF's data.

• Used QUARTZ and PyCharm to build up “Support Tool” API and features.

• Developed functionalities to check the ETF’s as well as the Price Source in SOD (Start Of Day) by comparing the list of ETF’s present in Lynx API against what the companies delivered (BlackRock AKA iShares, Invesco AKA PowerShares, StateStreet AKA SPDR, Vanguard AKA Vanguard), mainly from 3 different sources (Legacy, ATA, Impala).

• Developed functionality to connect to various host sources in order to check for files and their thresholds for each company (CSV or XLSX format) for both ETF and Price Source.

• Developed a dynamic knowledge graph using D3 to display each architect's dependency, also making use of CSS, HTML, FLASK, and Rest to request the information.

• Developed a Dependency module that received 3 attributes (API Name, Environment and Region), and based on them the module returns every possible dependency related to it along with basic functionalities to retrieve information from a specific section in the API.

• Used QUARTZ and PyCharm platform to develop Unit Test for various modules related to “MultiBasket” and “ETF Multi Basket Submission” API’s.

• Developed enhancements and gave maintenance to MicroServices for “MultiBasket” and “ETF Multi Basket Submission” API’s.

• Used TC (Test Complete) to develop UI Regression tests for “MultiBasket” and “ETF Multi Basket Submission” API’s, as well as created test cases and running it automatically every morning.

• Developed Python to extract final results from TC from the JavaScript Logs and publish them on a wiki page.

Developed a pivot table for Intraday Risk data using FLASK, Python, and UI Grid (AngularJS). Responsible for developing functionalities.

• Used QUARTZ platform to develop the dashboard and with it managed to create the database connections to access the Intraday Risk data which also allowed data to be retrieved and manipulated fast enough to meet the demands of the business.

• Build queries in SQL to retrieve information from SANDRA in order to evaluate Intraday Risk data.

• Grouping feature which allowed the user to group rows together based on similar values in specific columns, providing an effect similar in some ways to an Excel pivot table. The columns that weren't grouped by would be aggregated, providing for example a running count of the number of rows in each group.

• Expand / Contract and aggregation by group-level features.

• Single filter box feature that searched across multiple columns in the grid.

• Multiple filter fields feature for each column.

• Date filter feature which would bring back data based on the date selected by the user.

• Condition filter feature which defines how rows are chosen as matching the filter term (<,<=,>,>=,<>).

• Customize CellClass feature display based on the numeric value, green if the value is greater then zero, red if the value is less than zero, and gray if the value is equal to zero.

• Dynamic Grid resize feature based on the size of the browser.

• Drilldown feature for each column cells that weren't grouped where the user could click at any cell and depending on the tree level the Grid would open a Modal showing in detail the contents of the cell value based on the filter items of each tree level.

• Save / Restore feature that allowed the user to save the current look of the Grid and restore it upon returning to the Grid.

• Add / Remove and Hide / Display columns feature.

• Sort column rows feature (ASC / DESC).

• Column moving and resize feature.

• Export data Grid to Excel sheet or PDF file.

• Unit testing developed for each method created on the Backend (Python code).

• Applied TDD and CI for each module developed.

Responsible for providing development, maintenance, and support to Quantum Application System such as attending enhancements, incidents, and requests from users in Django/Python, following Agile Methodology in new version release, creating unit testing for each enhancement in the upcoming version, administrating the database in ORACLE and creating the interface between other applications.

• Delivered 5 versions of the system application called Quantum.

• Developed enhancements and gave maintenance to MicroServices in Django for Quantum API (such as contracts, tracking, alarms, currency)

• Work closely with business analysts, quantitative research teams, and business users to interpret the requirements and evaluate alternative solutions.

• Create technical design recommendations for developing and integrating programs per written specifications.

• Perform unit testing and system integration testing of the newly developed functionality.

• Examine applications to ensure adherence to Application Engineering guidelines, processes, and procedures.

• Implement and test modifications to existing application modules in accordance with application support and industry standard.

• Evaluate service-level issues and suggested enhancements escalated by the Service Delivery Team to diagnose and address underlying system problems and inefficiencies.

• Dealt with meetings with other system owners to solve issues related to all of us in which full knowledge of Quantum and the other systems was required in order to solve the issue.

• Established and developed interfaces between other systems as well as the conditions either to receive data in XML format or send monthly reports in a text with specific data from the DB.

• Solve current issues within Quantum such as upload files that were being saved with incorrect values, when creating a Transaction this would use the exchange from the Contract related to it, including leading zeros in reports when exporting them to Excel format, developed an algorithm that would compare the accruals from 2 reports that are monthly created, and so on.

• Attended requests from users such as making customized changes in specific modules in Quantum, added extra information in reports, delivered reports related to current users that were admin and superusers in Quantum, removed data from Quantum's DB in order to make the monthly close correct since sometimes entries were incorrect, and so on.

• Developed enhancements in Quantum for each version release such as adding new ways to search for data based on different inputs, added dynamic filters using AJAX, automatically update data whenever new data came from another system through the interface connection between them, added an auto-fill form whenever a Vendor was selected when creating a Contract, included data in statistical diagram, added new field in DB named as “employee type” and included it in all reports, and so on.

• Dealt with users by having meetings with them in order to fully understand what exactly they wanted for their requirements.

• Dealt with DB error that was caused by another system that sends incorrect data into Quantum, analyzed how many records were affected, how many of them got overwritten and how many of them were created, established a DB backup previous to the incident day and developed a Python script that would reverse the all the records as they were.

• Followed Software Development method “Agile” for each Quantum version release and also updated all documents that were affected by the enhancements such as CII (Configuration Item Inventory), Database Design, Detailed Design, Interface Design and URS (User Requirements Specifications), as well as to prepare other required documents such as SIQ (Software Installation Qualification), SCS (System Certification Summary) and UT (Unit Testing).

• TDD and CI were applied for each version release of the application.