Data Solution Architect

Leverage analysis and design techniques to solve business problems using information technology to operationalize data and analytical models and drive long-term business results.

• Partner with MDS to provide accessibility retrievability security and protection of data in an ethical manner.
• Partner with Product Owners BI Developers and Business Leads to conduct business requirement gathering and continuous improvement sessions to support the business understand requirements for analytical projects and develop necessary requirement documents and acceptance criteria to support their development in line with process guidelines.
• Develop UAT (User Acceptance Testing) and SIT (System Integration Testing) test cases based on analytical data product requirements.
• Support the scoping building testing and maintenance of transport/data pipelines and the retrieval of applicable data sets for specific use cases.
• Support the building testing and maintenance of data models with the flexibility to change when business requirements change while also reconciling multiple logical source models into a single logically consistent model.
• Analyze the structure format and reliability of new and existing data sources considering factors such as data integrity completeness and accuracy and drive continuous improvement.
• Participate in data governance processes to ensure data is properly maintained and documented for reusability by the business.
• Understand data and metadata to support consistency of information retrieval combination analysis pattern recognition and interpretation.

A desire to drive your future and accelerate your career along with the following experience and knowledge:

• Understanding of Data Engineering concepts within a business setting including working with multiple systems such as SAP and internal and external data sources. Experience in developing enhancing testing and maintaining data products.
• Experience using a diverse range of languages and tools including scripting languages for data extraction transformation storage processing and integration.
• Ability to analyze business requirements as a guide for data modeling and apply data analysis design modeling and quality assurance techniques and continuous improvement based on a detailed understanding of business processes to establish modify or maintain data structures and associated components including entity descriptions relationship descriptions and attribute definitions.
• Ability to simplify complex problems and effectively communicate technical concepts to a diverse audience.

• Cloud computing technologies: Azure GCP
• Programming Languages: SQL Python PySpark (Apache Spark) DAX etc.
• Analytics platforms: Databricks Google Cloud Dataproc etc.
• Experience with CI/CD DevOps and DataOps techniques.
• Experience with ETL data pipelines and architecture.
• Technical documentation.
• Experience in data modeling and wrangling techniques and tools including Star Schema Snowflake Schema Data Vault Alteryx Power BI Tableau etc.
• Data quality and profiling methods.

• Bachelors degree in a related field.
• BS Computer Science Information Systems etc.

• 1 years of Data Engineering/Modeling experience.
• 3 years of Database Design experience.