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Data Engineer Resume

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SUMMARY:

It is my desire to pursue a position in which I can think critically to pursue solutions while continuing to learn and develop a broader skill set.

SKILLS:

  • Programming Languages:
  • Python
  • SQL
  • PL - SQL
  • Java
  • PHP
  • JavaScript
  • C#
  • ASP.NET
  • ETL with SSIS
  • Data Modeling
  • Predictive Analytics
  • Business Intelligence KPIs
  • Healthcare Data knowledge
  • SVN/GIT Version Control
  • Amazon AWS Administration
  • Regular Expressions
  • Android App Development

EXPERIENCE:

Confidential

Data Engineer

Responsibilities:

  • Identified and provided solutions to client inquiries by reviewing data with efficient SQL queries.
  • Wrote PL/SQL scripts to perform bulk corrections to the client’s data to resolve data integrity issues.
  • Reviewed, debugged, and maintained Ruby scripts used to import and process from various healthcare data sources.
  • Utilized Python Data Science libraries to analyze client’s fiscal data to forecast future spending, profits, and generate reports of recommendations to decrease hospital drug expenditure.
  • Knowledge of the creation of regular expressions needed to generate patterns to successfully parse data files.
  • Reviewed and debugged PHP and JavaScript code used to generate reports and pull data to the client's dashboard.
  • Worked major projects regarding patient data correction to resolve issues generated by inconsistent client data.
  • Generated temporary data model schemas to allow for aggregation and partition logic to be applied to data subsets needed for additional analysis and data corrections.
  • Developed stored procedures and functions as tools for use by fellow analysts to resolve commonly occurring issues.
  • Utilized Amazon AWS to generate Ubuntu replications for use in testing of altered PHP and Javascript code blocks.

Confidential

BI ETL Developer

Responsibilities:

  • Developed, maintained and optimized ETL pipelines using Microsoft SSIS for a range of clients with large and diverse datasets from various industries including healthcare, liquor distribution, and retail.
  • Collaborated with fellow consultants to brainstorm and develop unique solutions for each client’s unique implementation.
  • Created data models to group together fields needed to generate important reporting calculations, reduce model size, and allow for quick data refreshes.
  • Developed map and reduce code to generate Python dictionaries for NoSQL data structure adherence.
  • Worked in both Linux and Windows environments to implement solutions in the clients existing infrastructure.
  • Utilized Confidential tools to automate script runs, file backups, and data model refreshes.
  • Set up file systems, directories, and filename patterns to organize client data, models, and ad-hoc reports for ease of use.
  • Maintained correspondence with clients throughout the development cycle to explain progress of the implementation.
  • Developed Python scripts to parse client data and shell scripts to manage and support software execution.
  • Produced detailed documentation of each implementation for the client's reference.
  • Maintained Perl scripts used to configure access control per file type and dynamically configure report headers.
  • Analyzed existing data trends to forecast future data progression and recommend goals.

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