Data Architect Resume

TECHNICAL SKILLS

Digital Data Integration and Transformation Cloud - Based Modern Data Architectures-Data
Ingestion, Data Warehouse, Data Lakes and Cloud Analytics
Data Analytics - Predictive, Prescriptive and Descriptive
Data preparation for Artificial Intelligence and Business Intelligence
Project Management
Data Quality and Data Governance
Data Modeling
Data Integration
Data Warehousing
Data Management
Data Migration
Data Virtualization
Data Catalog
ETL/ELT

PROFESSIONAL EXPERIENCE

Confidential

Data Architect

Responsibilities:

Assessed application portfolios and design reliable and cost-effective data architectures by understanding customer's business drivers.
Led and Collaborated with other Architects, Developers and business partners to provide technical design guidance to align with strategy and applicable technical standards.
Defined, designed and developed an implementation plan for IoT Digital Data Analytics solution for leading Life Sciences Client using Azure components namely Event Hubs, Stream Analytics, Azure Data Lake, Azure SQL Database and Power BI.
Collaborated on Cloud Vision by providing thought leadership on cloud infrastructure and cloud services to meet the operational objectives for an integrated cloud solution.
Environment: Azure Event Hubs, Stream Analytics, Azure Data Lake, Azure SQL Database.

Confidential

Data Architect

Responsibilities:

Conducted discovery workshops with key business units/stakeholders to solicit a perspective of the As Is' state for the use.
Assessed the Data Architecture of the system and the Platform Maturity.
Created strategy, short-term and long-term roadmaps with the necessary planning tool to guide initiatives that created and improved business & technical capabilities to support the company by best-leveraging data assets to realize business goals.
Provided design guidance follows the enterprise architecture vision and adheres to applicable application technology guidelines.
Established BI Framework and Governance Plan as a long-term roadmap.
Understood the data sources, types of analytics and are needed for platform strategy and planning.
Re-planning of existing EDW data model involved schema design considerations, de-normalization, partitioning and methods for loading data into Google Big Query.
Re-design current normalized star schema on Oracle based Data warehouse to target de-normalized table datasets on Big Query.

Confidential

Technical Consultant

Responsibilities:

Devised conceptual, logical and physical data models and high level and low-level documentation.
Reviewed business requirements and documented ETL process design including source to target mappings, data dictionaries and transformations by interacting directly with the client.
Designed complex Microsoft SQL Server Integration Services (SSIS) packages to perform data extraction from various kinds of data sources (SQL Server, Oracle, Flat Files, Excel source files and XML files), data transformation and data loading to the target regulatory data warehouse.
Loaded target Data warehouse Dimension and fact tables by applying initial load/ongoing load processes using SCD, CDC, Parent/Child SSIS packages and Lookup, Script, Fuzzy Lookup, Derived Columns, Condition Split, Term Extraction, Aggregate and Pivot Transformation.
Written complex stored procedures, triggers, user-defined functions, views and cursors for handling business logic and functionality of various modules. Executed Error Handling using Event Handlers in SSIS packages and notified process results to the business owners.
Carried performance tuning and proactive optimization of SSIS Packages. Version control was implemented with Tortoise SVN and the jobs were scheduled using Tidal Enterprise Scheduler tool.
Developed and delivered within an agile Scrum framework.

Environment: Microsoft SQL Server Integration Services (SSIS) 2012, Oracle PL/SQL, Microsoft SQL Server 2014, Microsoft Visual Studio C#, Tidal Enterprise Scheduler 5.3.1, Tortoise SVN, SQL Data Modeler 17.0,Jira.

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