Senior Data Engineer Resume Chicago, IL - Hire IT People

SUMMARY

Over 13 plus years of extensive experience in Data Analysis, Business Intelligence, Development, and Design.
Application Development, Implementation and Maintenance experience within the Salvage, Financial Services/Investment, Insurance, Healthcare, and Auto industries.
Software Design/Development skills with extensive experience in Power BI, Azure Data Factory, Azure Analysis Service, Azure Datawarehouse, Azure Databricks, Azure DevOps, Microsoft SQL Server Reporting Services (SSRS), SQL Server Analysis Services (SSAS), and SQL Server Integration Services (SSIS).
Proficient in Python, JavaScript, CSS and HTML.
Expertise in Client/Server applications using SQL Server and Oracle.
Extensive use of SharePoint for reporting and collaboration.
Expertise in developing and publishing reports of various types using Power BI, SSRS and Business Objects.
Ability to understand long - term project development issues at all levels, from interpersonal relationships to details of coding scripts.
A strong team member with solid communication and analytical skills.
Experience implementing Data Science using Python libraries such as PySpark, NumPy, SciPy, Matplotlib and Pandas .
Proficient in developing SOAP and RESTful Web Services.

TECHNICAL SKILLS

Operating Systems: Windows, Linux

Tools: Azure Data Factory, Azure Databricks, Azure Lake Gen2, Microsoft BI full stack, Power BI, SharePoint, BusinessObjects 5.x/6.x,XIr2/XIr3, Dashboard, SSIS, SSAS, SSRS

Programming: SQL, Python, JSP, CSS, HTML

Databases: Azure SQL database, Azure Synapse, SQL Server 2017/2016/2012/2008 R2/2005, Oracle

Database Tools: Data Science - Python, Stored Procedures, Database Triggers, and Packages

PROFESSIONAL EXPERIENCE

Confidential - Chicago, IL

Senior Data Engineer

Responsibilities:

Design DW based on Delta lake tables and use spark connection for PowerBI reporting.
Build Azure Data Factory load using piplines and Dataflow.
Setting up Clusters and jobs for Azure Databricks.
Write scala and python script notebooks for Azure Databircks transformation task.
Build a central scheduling system for all Azure Components using Azure Data Factory.
Build Power BI Datasets and Reports.
Setup auditing capabilities for Power BI system.
Conduct performance tuning at database level
Conduct daily status meetings with Onshore and Offshore teams.

Technologies Used: Azure Data Factory, Azure Databricks, Azure Gen Lake2, Azure SQL DB, Azure Synapse, SQL Server 2016/2014, Teradata, SharePoint Office 365, Power BI, SSIS, SSRS, Azure DevOps

Confidential, IL

Solutions Architect/Data Engineer

Responsibilities:

Performance Tuning on the backend SQL query and frontend SSAS Tabular model saved 2 hours in the initial processing time.
Implemented POC to load all company data in Azure Lake Gen2 and further load into Azure Datawarehouse using Polybase.
Implemented Core Model strategy which involved creation of one core data model using SSAS for each of the departments in Confidential . This eliminated knowledge gaps, ensured all reports came from a single source of truth and maximized the ROI on time spent constructing the best data model, best transformations.
Proposed moving Power BI Licensing from P1 to P2 after Power BI capacity analysis considering factors like data models used, the number of queries and their complexity, the hourly distribution of the usage of the service, the data refresh rates.
Proposed conversion of all individual business department specific Multi-dimensional cube to a centralized SSAS Tabular model. This saved initial data processing time plus BI report performance was enhanced. This was also done to adhere to the principle of Single source of truth (SSOT) concept.
Build complex Power BI report and develop SSAS tabular model as source for Power BI reports.
Performed monitoring, disaster recovery, backup, automated testing, automated schema migration, and continuous deployment.
Build meaningful visualizations, dashboards, scorecards and reporting solutions to empower users to create, collaborate, and benefit from insights gained through analytics.
Create Metrics master score cards and dashboards, reports using with Microsoft Power BI Desktop premium and SQL SERVER Reporting Services.
Build Key Performance Indicators KPI based on Number of available metric's, generate KPI based trend reports.

Technologies Used: Azure Data Factory, Azure Databricks, Azure Gen Lake2, Azure SQL DB, SQL Server 2016/2014, Power BI, SSAS, SSIS, SSRS, SharePoint Office 365, MS Team Foundation

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Senior Data Engineer Resume

Chicago, IL

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