Matillion SSIS

Matillion, SSIS and snowflake:

Matillion:

• Design, develop, and maintain ETL processes using Matillion to extract, transform, and load data into Snowflake and Develop and Debug ETL programs primarily using Matillion Cloud.
• Collaborate with data architects and business stakeholders to understand data requirements and translate them into technical solutions.
• We seek a skilled technical professional to lead the end-to-end system and architecture design for our application and infrastructure.
• Data validation & end to end testing of ETL Objects, Source data analysis and data profiling.
• Troubleshoot and resolve issues related to Matillion development and data integration.
• Collaborate with business users to create architecture in alignment with business need.
• Collaborate in Developing Project requirements for end-to-end Data integration process using ETL for Structured, semi-structured and Unstructured Data.
• Strong understanding of ELT/ETL and integration concepts and design best practices.
• Experience in performance tuning of the Matillion Cloud data pipelines and should be able to trouble shoot the issue quickly.
• Experience in Snowsql, Snow pipe will be added advantage.
• Follow best practices for Matillion development to ensure maintainability, scalability, and reusability of ETL processes.

Required Non-Technical Skills:

• Excellent presentation and communication skills for interacting with both technical and non-technical stakeholders.

Resilience and the ability to thrive in a dynamic, fast-paced work environment are essential.

SSIS:

An MS SSIS (Microsoft SQL Server Integration Services) Developer is responsible for designing, developing, and maintaining ETL (Extract, Transform, Load) processes within the Microsoft SQL Server environment. SSIS is a powerful tool used for data integration and workflow applications. Here are the common roles and responsibilities associated with the position of an MS SSIS Developer:

1. **Requirement Analysis:**

- Collaborate with business analysts and stakeholders to understand data integration requirements.

- Analyze source and target systems to determine data transformation needs.

2. **ETL Design and Development:**

- Design and develop ETL processes using SSIS to extract, transform, and load data from source systems to target databases.

- Create and optimize data mappings, transformations, and workflows.

3. **Data Modeling:**

- Design and implement logical and physical data models that support ETL processes.

- Collaborate with data architects and database administrators to ensure effective data storage and retrieval.

4. **Data Cleansing and Transformation:**

- Implement data cleansing, validation, and transformation rules within SSIS packages.

- Handle data quality issues and ensure accurate data in the target systems.

5. **Package Deployment and Execution:**

- Deploy SSIS packages to SQL Server Integration Services Catalog or file system.

- Schedule and execute SSIS packages to ensure timely and automated data processing.

6. **Error Handling and Logging:**

- Implement error handling mechanisms within SSIS packages to address issues during data integration.

- Configure logging to capture information about package execution and errors.

7. **Performance Tuning:**

- Identify and address performance bottlenecks in SSIS packages.

- Optimize SQL queries, transformations, and package configurations for better performance.

8. **Integration with Other Systems:**

- Integrate SSIS with various data sources, databases, and external systems.

- Collaborate with system and application developers for seamless data flow.

9. **Security and Compliance:**

- Implement security measures to protect sensitive data during the ETL process.

- Ensure compliance with data governance and regulatory requirements.

10. **Parameterization and Configurations:**

- Parameterize SSIS packages to allow for dynamic configurations.

- Implement configurations to manage different environments (development, testing, production).

11. **Version Control:**

- Implement and maintain version control for SSIS packages.

- Ensure proper documentation and annotation within version control systems.

12. **Documentation:**

- Create and maintain comprehensive documentation for SSIS packages, including data mappings, transformations, and workflow designs.

- Document best practices and guidelines for SSIS development.

13. **Testing:**

- Conduct unit testing to validate the accuracy and efficiency of implemented ETL processes.

- Collaborate with quality assurance teams to perform system and integration testing.

14. **Troubleshooting and Support:**

- Identify and resolve issues related to SSIS development and package execution.

- Provide support to end-users and address inquiries related to SSIS functionality.

15. **Training:**

- Provide training to end-users and other stakeholders on using SSIS tools and accessing data integration solutions.

- Offer guidance on best practices for SSIS development.

An MS SSIS Developer plays a vital role in ensuring the effective and efficient movement of data within an organization's data ecosystem. Their responsibilities cover the entire ETL process, from requirement analysis to package deployment and execution, contributing to the overall success of data integration initiatives.

Snowflake experience/Skills:

A Snowflake Developer job description typically involves designing, developing, and maintaining data solutions within the Snowflake data platform. Key responsibilities include building data warehouses, data lakes, and data models, implementing data migration strategies, and ensuring solution quality through testing and debugging. Additionally, Snowflake Developers may be tasked with troubleshooting, providing technical support, and staying up-to-date with the latest Snowflake features and best practices

• Data Modeling and Design:

  Designing and implementing data models, including data warehousing, data lakes, and data modeling solutions.

• Data Migration:

  Participating in the design and implementation of data migration strategies.

• SQL Development:

  Writing, optimizing, and maintaining complex SQL queries.

• Data Transformation:

  Developing and implementing data transformation solutions based on designs.

• Data Integration:

  Integrating Snowflake with other tools and platforms.

• Performance Tuning:

  Tuning and optimizing Snowflake performance.

• Troubleshooting and Support:

  Providing technical support, troubleshooting issues, and resolving production problems.

• Documentation:

  Creating and maintaining documentation for data models, architecture, and processes.

• Collaboration:

  Collaborating with data scientists, BI developers, and analysts.

• Security and Compliance:

  Understanding and implementing security measures and compliance requirements within Snowflake.

• Data Ingestion:

  Experience with data ingestion into Snowflake, such as Snowpipe