NET Developer with Data analytics

Seeking experienced NET Developer with Advanced Data analytics and visualization engineer. Responsible for analyzing and interpreting complex data sets, using statistical and machine learning techniques to uncover insights and drive business decisions.  Experience  with various coding languages including ETL tool, SQL/T-SQL, Python, and Data Warehouse and Machine learning platform (Alteryx, Cloudera, snowflake) with extensive knowledge of web-based application including web services/API’s.

Interview: Teams

Location: Columbus, OH

Posting: 706574

Work: Hybrid

Role and Experience       

• 7 years of Application Development in Microsoft .NET,
• 7 years of Oracle/SQL Database
• 7 years of SQL script
• 7 years of API designs in RESTful, XML, XSLT, JSON, jQuery.
• 5 years of Python and/or other ETL tools
• 5 years of SQL/T-SQL
• 5 years of PL/SQL Experience
• 3 years of Alteryx, Cloudera, Snoflake
• 3 years of PowerBI, Denodo
• Excellent analytical skills, attention to detail, and problem-solving skills.
• Proven ability to handle multiple tasks and projects simultaneously.
• Familiar with the Agile Methodology.
• Working experience in Database & application performance tuning.
• Must possess excellent written and oral communication skills.
• Working experience in delivering expected results in unstructured environments.
• Works productively and effectively independently without significant management oversight.
• Identifies data sources, develop and maintain data architectures, constructs data catalog and data decomposition diagrams, provide data flow diagrams and documents the process.
• Develop conclusions and articulate implications of advanced data analytics results
• Ability to data mining/sourcing to be self-sufficient in the production of valuation and the analysis of business cases and ad-hoc requests.
• Ability to extract data from multiple data resources; remove corrupted data and fixing coding errors and related problems
• Ability to perform analysis to assess the quality and meaning of data; filter data by reviewing reports and performance indicators to identify and correct ode problems.
• ability to create compelling data visualizations and communicate insights effectively to technical and non-technical stakeholders is essential for data scientists.
• Using tools to identify, analyze, and interpret patterns and rends in complex data sets could be helpful for the diagnosis and prediction
• Preparing reports for the management stating trends, patterns, and predictions using relevant data in visualization.
• Work with developer and management to identify process improvement opportunities, propose system modification, and devise data governance strategies.
• Define and capture metadata and rules associated with ETL processes in various application
• Establish methods and procedures for tracking data quality, completeness, redundancy and improvement; and processes for governing the identification, collection and use of corporate metadata to assure metadata is accurate and valid in the business intelligence environments.