Data Solution Architect

Job Description

Job Description

Summary:

• Work Mode: Remote
• Hours: 8:00 AM - 5:00 PM

• 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 ensure accessibility, retrievability, security, and protection of data ethically.
• Collaborate with Product Owners, BI Developers, and Business Leads to gather business requirements and support continuous improvement sessions.
• 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 retrieval of applicable data sets for specific use cases.
• Support the building, testing, and maintenance of data models with flexibility for changing business requirements.
• Analyze the structure, format, and reliability of new and existing data sources to drive continuous improvement.
• Participate in data governance processes to ensure data is properly maintained and documented for reusability.
• Understand data and metadata to support consistency of information retrieval, combination, analysis, pattern recognition, and interpretation.

• 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.
• Proficiency in using a diverse range of languages and tools for data extraction, transformation, storage, processing, and integration.
• Ability to analyze business requirements for data modeling and apply data analysis, design, modeling, and quality assurance techniques.
• Ability to simplify complex problems and communicate technical concepts to a diverse audience.

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

• Bachelor’s degree in a related field.
• BS in Computer Science, Information Systems, etc.

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