Data Analyst Resume

SUMMARY

A goal - oriented professional with over 7.6 years of experience in Information Technology
Strong in Data Warehouse design, develop and analytics.
Extensive experience in design and development of ETL in Data Stage with all versions
Strong in programming of shell, python and proficient in all RDBS tools like Teradata, Oracle, SQL Server and Mysql Db2.
Experience in various platforms and technologies: Analytics, Hadoop, spark
Experience in Data modeling and designing
Experience in Cloud computing and Microsoft Azure cloud service.
Experienced in GitHub CI and Jenkins for CI and for End-to-End automation for all build and CD.
Good Knowledge on Apache Spark with Python, Airflow, Data bricks, Jupyter, Hadoop Big Data.
Experience with Agile/Scrum methodology
The ability to present and absorb complex ideas quickly and accurately.
Strong focus on time-management, decision-making, and project delivery.
Excellent Knowledge of Application Lifecycle Management, Change & Release Management and ITIL process.
Exposed to all aspects of software development life cycle (SDLC) such as Analysis, Planning, Developing, Testing, implementing and Post-production analysis of the projects.
Good interaction with developers, managers, and team members to coordinate job tasks and strong commitment to work.

PROFESSIONAL EXPERIENCE

Confidential

Data Analyst

Responsibilities:

Providing Application development and support for expertise for its Case Management Application Development
Develop Datawarehouse model for the backend database for reporting requirements as per state and Federal Health and Human Services agencies.
Developed Data (Core ETL) extraction model for easy end user data reporting UI interfaces.
Created multiple pipelines and activities and activities for full and incremental data loads into Azure Data Lake store and Azure Synapse.
Designing and implementing redundant systems, policies, and procedures for disaster recovery and data archiving of data asserts.
Worked on (Coding, Review, Unit testing, debugging & deployment & Operations & Support) and maintain Azure Data Factory service
Worked on ETL package for data migration from internal source system to Azure cloud
Design specifications, installation instructions, implementation guidelines and other system-related information.

Confidential

Sr. Data Engineering Analyst /Hadoop Developer

Responsibilities:

Collaborate with Business Analysts to gather business requirements, evaluate the scope of design and technical feasibility.
Analyze complexity and technical impact of requirements to cope with the existing design and discuss with Business Analyst for further refinement of requirements.
Created High Level and Detailed Level Design. Conduct design reviews and design verification. Create final work estimate.
End-to-end implementation, maintenance, optimizations and enhancement of the application.
Code Review, Presenting code & design in Technical Review Board
Leading the team and ensuring the delivery happens on time with the best quality and least defects. This is important in living up to the Quality standards of Optum.
Used Import and Export in Web Infosphere Server Manager for importing the importing and exporting jobs/projects1 1 5
Verify production code, support first three executions of code in production, Transition of the code and Process to the Maintenance/Support team.
Co-ordinate with various Business partners, Analytical teams, Stakeholders to provide status reporting
Actively participated in the team meetings in day to day calls, meeting reviews, status calls, batch reviews, etc.

Environment: Teradata TD14, Data Stage 8.5, Unix/Linux, DB2 v10.1, TWS, HPSM, Mercury ITG,SQL,BTEQConfidential

Data Engineering Analyst /ETL Developer

Responsibilities:

Extensively used DataStage Designer and Teradata to build the ETL process which pulls the data and does the grouping techniques in job design.
Developed master jobs (Job Sequencing) for controlling flow of both parallel & server Jobs.
Good knowledge in parameterizing the variables rather than hardcoding directly, Used Director widely for monitoring the job flow and processing speed.
Based on the above analysis did performance tuning for improving job processing speed.
Developed Autosys jobs for scheduling the Jobs. These job includes Box jobs, Command jobs, file watcher jobs and creating ITG requests.
Closely monitor schedules and look into the failures to complete all ETL/Load processes within the SLA.
Designed and developed SQL scripts and extensively used Teradata utilities like BTEQ scripts, Fast Load, Multi Load to perform bulk database loads and updates.
After Completing ETL activities corresponding load file will be sent to Cube team for building Cubes.
Created spec doc’s for automating the manual processes.
Closely work with On-shore people and Business people to resolve critical issues occurred during load process.
Later all the UGAP jobs were migrated from Autosys to TWS, we were involved in end to end migration process and migrated successfully