Shiva Kumar Jalabagari

• Data Pipeline Development:
  
  Design, develop, and maintain data pipelines for ingesting, processing, and transforming large volumes of data.
  Use Apache Spark for distributed data processing, leveraging its RDDs, DataFrames, and Datasets APIs.
  Develop ETL (Extract, Transform, Load) processes to extract data from various sources, transform it into a usable format, and load it into data warehouses or data lakes.
  
• Data Modeling and Architecture:
  
  Design and implement data models and architectures to support efficient data storage, retrieval, and analysis.
  Optimize data storage formats and partitioning strategies for performance and scalability.
  Implement dimensional modeling for data warehousing solutions using concepts such as star schema and snowflake schema.
  SQL Querying and Optimization:
  
  Write and optimize SQL queries for data analysis, aggregation, and reporting.Use window functions, joins, and subqueries to manipulate and analyze data effectively.Optimize SQL queries for performance by analyzing query execution plans and indexing strategies.
  
• Python/Scala/SQL Programming:
  
  Useing programming language for scripting, data manipulation, and automation tasks.
  Develop custom data processing logic and algorithms using Python libraries such as Pandas, NumPy, and SciPy.
  Integrate Python code with Spark applications using PySpark for distributed data processing.
  Data Quality and Governance:
  
  Implement data quality checks, validation rules, and data governance policies to ensure the accuracy and integrity of data.
  Monitor and address data quality issues through data profiling, cleansing, and validation processes.
  Implement data lineage and metadata management solutions to track the flow and usage of data.
  
• Infrastructure Management:
  
  Provision and manage cloud infrastructure resources using AWS, Azure, or GCP services such as AWS EMR, Azure HDInsight, or GCP Dataproc.
  Optimize infrastructure configurations for cost-effectiveness, performance, and scalability.
  Automate infrastructure provisioning and deployment using infrastructure-as-code tools such as AWS CloudFormation, Azure Resource Manager (ARM) templates, or GCP Deployment Manager.
  
• Collaboration and Documentation:
  
  Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
  Document data pipelines, architectures, and processes to facilitate knowledge sharing and maintainability.
  Conduct code reviews and provide feedback to team members to ensure code quality and adherence to best practices.
  
• Performance Monitoring and Optimization:
  
  Monitor the performance and health of data pipelines and infrastructure components using monitoring and logging tools provided by AWS, Azure, or GCP.
  Analyze performance metrics and identify bottlenecks or areas for optimization.
  Optimize data processing workflows, SQL queries, and infrastructure configurations to improve performance and efficiency.

Requirements Analysis: Collaborate with business stakeholders, data analysts, and other team members to gather and analyze requirements for data integration projects. Understand business processes, data sources, and integration needs to design effective solutions.

Data Integration Design: Design data integration workflows, mappings, and transformations using Informatica PowerCenter or other Informatica products. Define data mappings, transformations, and business rules to extract, transform, and load (ETL) data from source systems to target systems.

Development and Implementation: Develop and implement data integration solutions using Informatica PowerCenter. Configure source and target connections, create mappings, workflows, sessions, and workflows, and schedule data integration jobs.

Data Quality and Cleansing: Implement data quality and cleansing processes to ensure the accuracy, completeness, and consistency of data. Use Informatica Data Quality (IDQ) or other data quality tools to profile, cleanse, and standardize data.

Performance Tuning and Optimization: Optimize data integration workflows, mappings, and transformations for performance and efficiency. Identify and address performance bottlenecks, optimize SQL queries, and fine-tune session and workflow configurations.

Metadata Management: Manage metadata for data integration processes, including data lineage, impact analysis, and version control. Document data integration workflows, mappings, and transformations to facilitate knowledge sharing and maintainability.

Error Handling and Monitoring: Implement error handling and logging mechanisms to track data integration errors, exceptions, and failures. Monitor data integration jobs, troubleshoot issues, and resolve errors in a timely manner to ensure data integrity and availability.

Collaboration and Documentation: Collaborate with cross-functional teams including data architects, database administrators, and business analysts to design and implement data integration solutions. Document data integration requirements, designs, and processes to facilitate communication and knowledge sharing.

Compliance and Security: Ensure compliance with data governance policies, regulatory requirements, and security standards. Implement data encryption, access controls, and auditing mechanisms to protect sensitive data and ensure data privacy and security.

Continuous Learning and Improvement: Stay updated on emerging technologies, best practices, and trends in data integration and Informatica tools. Participate in training programs, workshops, and conferences to enhance your skills and knowledge in data integration and Informatica development.

Data Integration Design: Design data integration workflows, mappings, and transformations to extract, transform, and load (ETL) data from source systems to target systems. Define data mappings, transformations, and business rules based on requirements provided by business stakeholders and data analysts.

Development and Implementation: Develop and implement data integration solutions using Informatica PowerCenter or other Informatica products. Configure source and target connections, create mappings, workflows, sessions, and workflows, and schedule data integration jobs.

Data Quality and Cleansing: Implement data quality and cleansing processes to ensure the accuracy, completeness, and consistency of data. Use Informatica Data Quality (IDQ) or other data quality tools to profile, cleanse, standardize, and enrich data as it moves through the data integration pipeline.

Performance Tuning and Optimization: Optimize data integration workflows, mappings, and transformations for performance and efficiency. Identify and address performance bottlenecks, optimize SQL queries, and fine-tune session and workflow configurations to improve data processing throughput and reduce execution times.

Error Handling and Logging: Implement error handling and logging mechanisms to track data integration errors, exceptions, and failures. Handle data integration errors gracefully, log error messages, and notify stakeholders of issues that require attention.

Metadata Management: Manage metadata for data integration processes, including data lineage, impact analysis, and version control. Document data integration workflows, mappings, and transformations to facilitate knowledge sharing, collaboration, and maintainability.

Scripting and Custom Development: Develop custom scripts, expressions, and functions to extend the functionality of Informatica PowerCenter. Use scripting languages such as Shell Scripting, Python, or JavaScript to implement custom logic and data transformations as needed.

Integration with Source and Target Systems: Integrate Informatica PowerCenter with various source and target systems such as relational databases, flat files, XML files, web services, and cloud platforms. Configure connections, drivers, and protocols to enable data extraction and loading from/to different data sources and destinations.

Testing and Validation: Conduct unit testing, integration testing, and user acceptance testing (UAT) to validate the functionality and performance of data integration solutions. Verify data accuracy, completeness, and consistency against predefined acceptance criteria and business requirements.

Documentation and Knowledge Sharing: Document data integration requirements, designs, configurations, and processes to facilitate knowledge sharing and collaboration among team members. Create technical documentation, user guides, and training materials for data integration solutions.

Continuous Learning and Improvement: Stay updated on Informatica product releases, updates, and best practices in data integration and ETL development. Participate in training programs, workshops, and conferences to enhance your skills and knowledge in Informatica development and data integration technologies.

Requirements Gathering: Collaborate with business stakeholders, data analysts, and project managers to understand data integration requirements. Gather requirements related to data sources, data transformations, business rules, and integration workflows.

Solution Design: Design data integration solutions based on the gathered requirements. Define data integration workflows, mappings, and transformations to extract, transform, and load (ETL) data from source systems to target systems. Design data models, schemas, and mappings to ensure efficient and effective data processing.

Development: Develop data integration solutions using Informatica PowerCenter or other Informatica products. Configure source and target connections, create mappings, workflows, sessions, and workflows to implement the designed solution. Write and maintain ETL code, scripts, and transformations using Informatica's visual development environment.

Testing: Conduct unit testing, integration testing, and system testing of data integration solutions. Verify data accuracy, completeness, and consistency against predefined acceptance criteria and business requirements. Identify and troubleshoot issues, errors, and performance bottlenecks in data integration workflows.

Documentation: Document data integration requirements, designs, configurations, and processes. Create technical documentation, user guides, and training materials for data integration solutions. Maintain documentation repositories and version control systems to ensure documentation accuracy and accessibility.

Deployment and Maintenance: Deploy data integration solutions to production environments and ensure smooth transition to operations teams. Monitor and maintain data integration workflows, mappings, and transformations in production. Perform regular maintenance activities such as backups, updates, and performance tuning to optimize system performance and reliability.

Collaboration: Collaborate with cross-functional teams including data architects, database administrators, business analysts, and quality assurance testers. Coordinate with project managers, team leads, and stakeholders to ensure alignment with project goals, timelines, and deliverables.

Continuous Improvement: Stay updated on Informatica product releases, updates, and best practices in data integration and ETL development. Participate in training programs, workshops, and conferences to enhance your skills and knowledge in Informatica development and data integration technologies. Proactively identify opportunities for process improvements and tool enhancements to optimize data integration workflows and achieve business objectives.

Requirements Gathering: Collaborate with business stakeholders, data analysts, and project managers to understand data integration requirements. Gather requirements related to data sources, data transformations, business rules, and integration workflows.

Solution Design: Design data integration solutions based on the gathered requirements. Define data integration workflows, mappings, and transformations to extract, transform, and load (ETL) data from source systems to target systems. Design data models, schemas, and mappings to ensure efficient and effective data processing.

Development: Develop data integration solutions using Informatica PowerCenter or other Informatica products. Configure source and target connections, create mappings, workflows, sessions, and workflows to implement the designed solution. Write and maintain ETL code, scripts, and transformations using Informatica's visual development environment.

Testing: Conduct unit testing, integration testing, and system testing of data integration solutions. Verify data accuracy, completeness, and consistency against predefined acceptance criteria and business requirements. Identify and troubleshoot issues, errors, and performance bottlenecks in data integration workflows.

Documentation: Document data integration requirements, designs, configurations, and processes. Create technical documentation, user guides, and training materials for data integration solutions. Maintain documentation repositories and version control systems to ensure documentation accuracy and accessibility.

Deployment and Maintenance: Deploy data integration solutions to production environments and ensure smooth transition to operations teams. Monitor and maintain data integration workflows, mappings, and transformations in production. Perform regular maintenance activities such as backups, updates, and performance tuning to optimize system performance and reliability.

Collaboration: Collaborate with cross-functional teams including data architects, database administrators, business analysts, and quality assurance testers. Coordinate with project managers, team leads, and stakeholders to ensure alignment with project goals, timelines, and deliverables.

Continuous Improvement: Stay updated on Informatica product releases, updates, and best practices in data integration and ETL development. Participate in training programs, workshops, and conferences to enhance your skills and knowledge in Informatica development and data integration technologies. Proactively identify opportunities for process improvements and tool enhancements to optimize data integration workflows and achieve business objectives.

Requirements Gathering: Collaborate with business stakeholders, data analysts, and project managers to understand data integration requirements. Gather requirements related to data sources, data transformations, business rules, and integration workflows.

Solution Design: Design data integration solutions based on the gathered requirements. Define data integration workflows, mappings, and transformations to extract, transform, and load (ETL) data from source systems to target systems. Design data models, schemas, and mappings to ensure efficient and effective data processing.

Development: Develop data integration solutions using Informatica PowerCenter or other Informatica products. Configure source and target connections, create mappings, workflows, sessions, and workflows to implement the designed solution. Write and maintain ETL code, scripts, and transformations using Informatica's visual development environment.

Testing: Conduct unit testing, integration testing, and system testing of data integration solutions. Verify data accuracy, completeness, and consistency against predefined acceptance criteria and business requirements. Identify and troubleshoot issues, errors, and performance bottlenecks in data integration workflows.

Documentation: Document data integration requirements, designs, configurations, and processes. Create technical documentation, user guides, and training materials for data integration solutions. Maintain documentation repositories and version control systems to ensure documentation accuracy and accessibility.

Deployment and Maintenance: Deploy data integration solutions to production environments and ensure smooth transition to operations teams. Monitor and maintain data integration workflows, mappings, and transformations in production. Perform regular maintenance activities such as backups, updates, and performance tuning to optimize system performance and reliability.

Collaboration: Collaborate with cross-functional teams including data architects, database administrators, business analysts, and quality assurance testers. Coordinate with project managers, team leads, and stakeholders to ensure alignment with project goals, timelines, and deliverables.

Continuous Improvement: Stay updated on Informatica product releases, updates, and best practices in data integration and ETL development. Participate in training programs, workshops, and conferences to enhance your skills and knowledge in Informatica development and data integration technologies. Proactively identify opportunities for process improvements and tool enhancements to optimize data integration workflows and achieve business objectives.