Data Solution Architect

Summary

The company is confidential and operates in data and analytics solutions. The Data Solution Architect will leverage analysis and design techniques to operationalize data and analytical models, partnering with business and technical stakeholders to develop data products, pipelines, models, testing, governance, and quality improvements.

Responsibilities

• 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

Skills

• 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
• Bachelor's degree in a related field
• BS Computer Science, Information Systems, etc
• 1+ years of Data Engineering/Modeling experience
• 3+ years of Database Design experience

Qualifications

Must Haves

• 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
• Bachelor's degree in a related field
• BS Computer Science, Information Systems, etc
• 1+ years of Data Engineering/Modeling experience
• 3+ years of Database Design experience