BHARANI KUMAR ALAPILLA SUDHAKAR

• Developed Python for data processing and testing tasks.
• Used Python to ensure data accuracy and quality.
• Designed, developed, and integrated Talend jobs with MongoDB and AWS for seamless data processing.
• Rewrote ETL jobs using AWS Step Functions and Lambda for optimized workflows.
• Utilized Starburst in AWS for efficient data querying and integration.
• Prepared unit test plans and collaborated with business stakeholders for validation.
• Fixed design and performance issues in ETL jobs and optimized Oracle SQL queries.
• Managed production and UAT issues, ensuring smooth operations across environments.
• Developed and deployed CI/CD pipelines for streamlined job deployments.
• Conducted integration testing and code reviews before moving jobs from Dev to QA and Production.
• Implemented best practices in data security, privacy, and scalability.
• Worked with stakeholders to define and align data engineering project requirements with business goals.
• Maintained documentation and provided training on best practices for handling structured and unstructured datasets.

• Gathered business requirements for the data warehouse and business intelligence reports for management.
• Scheduled parallel jobs using Control-M for efficient ETL workflow management.
• Utilized various Parallel Stages (Join, Lookup, Filter, Aggregator, Modify, Copy, Sort, Funnel, Change Data Capture, Remove Duplicates, Surrogate Key Generator, Row Generator, Column Generator, and Peek) for development and debugging.
• Developed ETL scripts using Java and Python for data transformation.
• Implemented SCD Type 1 and Type 2 using Teradata for historical data tracking.
• Designed and developed ETL processes to meet business requirements.
• Prepared unit test plans and reviewed them with business stakeholders for validation.
• Fixed existing design issues and fine-tuned ETL jobs to enhance performance.
• Resolved production and UAT issues to ensure smooth operations.
• Adapted ETL job design and development based on evolving business needs.
• Made functional changes to ETL processes in response to business requests.
• Conducted full integration testing and code reviews of jobs before deployment from Development to QA and Production environments.

• Developed technical solutions for the project based on business and technical requirements.
• Collaborated with DBA to implement the new table structure as per business requirements.
• Designed and developed ETL jobs using Talend, implementing SCD Type 1 and Type 2.
• Maintained code using SVN for version control in Talend.
• Converted DataStage jobs into Talend jobs in the data warehousing environment.
• Developed interfaces using IBM Infosphere DataStage 8.5 with DB2 as the data source/target.
• Coordinated with teams such as Network, Infrastructure, Information Security, and Architecture Governance for project support.
• Provided technical support and development activities to multiple Track/Portfolio teams.
• Addressed and resolved production and UAT issues to ensure smooth operations.
• Extensively used parallel stages (Join, Lookup, Filter, Aggregator, Modify, Copy, Sort, Funnel, CDC, Remove Duplicates, Surrogate Key Generator, Row Generator, Column Generator, Peek) for development and debugging.
• Conducted reviews with various stakeholders to ensure alignment on project goals and outcomes.
• Made functional changes based on business requests to meet evolving requirements.
• Deployed jobs to TST, Stage, and Production environments.

• Used IBM DataStage, Talend, Teradata, and Oracle for ETL processes and data integration.
• Integrated data from Tandem, Stratus, CMS, and EDW Table Games into Unified Business View (UBV) and data mart for reporting.
• Gathered business requirements for data warehousing and business intelligence reports.
• Developed and optimized ETL jobs in DataStage, Talend, and Teradata; implemented data loading processes
• Addressed data integrity issues, optimized ETL performance, and fixed production and UAT issues.

• Utilized IBM DataStage to connect to multiple servers and databases (Oracle, SQL ODBC, DB2) with MPP architecture for data processing.
• Loaded and transformed data into Softsolutions staging tables, applying business rules.
• Gathered business requirements for data integration and reporting.
• Responsible for designing and developing DataStage jobs, Unix scripts, and Control-M, coordinating with offshore teams.
• Extensively used parallel stages like Join, Lookup, Filter, Aggregator, Modify, Copy, Sort, Funnel, Change Data Capture, Remove Duplicates, Surrogate Key Generator, Row Generator, Column Generator, and Peek for development and debugging.
• Designed web service call jobs in DataStage.
• Fixed design issues, fine-tuned ETL jobs, and addressed production and UAT issues.
• Adapted ETL job design based on evolving business needs and made functional changes.
• Owned deliverables from source to target in DataStage.
• Migrated the ETL jobs from V7.5.1 to V7.5.3
• Preparation of test plans from smoke test cases to Regression test plans to ensure tracking and accomplishment of entire testing activities
• Preparing Mock up Data Based on Business Needs
• Fine Tuning the Long running jobs

Developed and maintained ETL jobs using IBM DataStage and UNIX shell scripts for data extraction, transformation, and loading.

Implemented data encryption to anonymize patient data before processing.

Used MFT tool to securely transfer encrypted data to IMS.

Third-Party Integration: Integrated data into ScriptPro TPMS to manage contract compliance and prescription reimbursement.

Managed and scheduled daily extraction of Sales, Drug, and Fiscal Calendar data feeds.

Automated job scheduling and managed data flows using Control-M.

Transformed and loaded data from Target RedRx stores into a sequential file for ScriptPro processing.

Conducted User Acceptance Testing (UAT) to ensure the system met business requirements.

Provided production support for troubleshooting and resolving production issues.

• Designed and developed ETL jobs using IBM DataStage to extract, transform, and load data from various source systems (Oracle, DB2) into the Data Warehouse. Ensured data integrity and applied necessary business rules.
• Managed and maintained databases (Oracle and DB2) used as sources and targets for ETL processes. Ensured efficient data storage and query performance.
• Created reports and dashboards using MicroStrategy for end-users to access data insights. Ensured the proper data modeling and schema design to support reporting needs.
• Integrated data from various source systems into the Data Warehouse using DataStage. Worked on data mapping, transformations, and scheduling for efficient data processing.
• Optimized ETL processes and SQL queries to enhance data loading times and reporting performance. Applied indexing and partitioning strategies in DB2 and Oracle for optimal performance.
• Developed and executed unit tests to validate ETL job transformations and data quality.
• Ensured data quality throughout the ETL process by performing data profiling and resolving data integrity issues.
• Used scheduling tools like Control-M to automate and manage ETL job execution. Ensured that data loads were executed timely and accurately.
• Deployed ETL jobs and reports to production environments and provided ongoing maintenance and troubleshooting support.
• Assisted end-users with understanding how to use reports and dashboards in MicroStrategy. Created documentation for ETL processes, data flow, and reporting structures.
• Worked closely with cross-functional teams, including business analysts, DBAs, and report developers, to gather requirements and provide effective data solutions.

• Marketing Analytics Application is one of the applications developed by TCS for Nielsen, which is being used by McDonalds (Nielsen's client)
• Presently Marketing analytics application is implemented only for McDonald's restaurants in U.K., Australia and Germany
• This application helps McDonald to monitor, analyze the sales of their restaurants all over the world
• This also helps McDonald to improve their business all over the world
• The Marketing Analytics Application processes the daily Point of sales (POS) Zip files received from McDonald's stores all over the world
• It validates Daily POS and sends the validated files to Nielsen Spoke server, which will later be loaded into Global Data warehouse
• Validation is done at different levels like file level validation, store level validation, menu item validation, business validation etc
• Production server maintenance and Monitoring the Jobs in the Data stage ETL, Ab Initio tools and Answering for user or client
• Creating jobs in Datastage
• Queries in the form of tickets and doing Analysis, work around for Bug fixing