Data Analyst II #26-21265

• Leverage analysis design techniques to solve business problems using information technology to operationalize data and analytical models to drive long-term business results.
• Partner with MDS in providing accessibility, retrievability, security and protection of data in an ethical manner.
• Parter with Product Owners, BI Developers and Business Leads to conduct business requirement gathering & continuous improvement sessions to support the business and 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 off analytical data product requirements.
• Support for scoping, building, testing, and maintaining transport/data pipelines and retrieving applicable data sets for specific use cases.
• Support building, testing, and maintaining 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, accuracy, and drive continuous improvement.
• Participate in data governance processes to ensure data is properly maintained and document for reusability by the business
• 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, internal and external data sources. Experience in developing, enhancing, testing, and maintaining data products.
• Experience in using diverse range of languages and tools, including scripting languages, for data extraction, transformation, storage, processing, and integration.
• Analyze business requirements as a guide for data modeling and apply data analysis, design, modeling, and quality assurance techniques, continuous improvement, based on a detailed understanding of business processes, to establish, modify or maintain data structures and associated components (entity descriptions, relationship descriptions, attribute definitions).
• Ability to simplify complex problems and effectively communicating technical concepts to a diverse audience.

More about this role

• 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 modelling and wrangling techniques and tools i.e., Star Schema, Snowflake Schema, Data vault, Alteryx, Power BI, Tableau, etc.
• Data quality and profiling methods

Education / Certifications:

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

Job specific requirements:

• 1+ years Data Engineering/Modeling
• 3+ years Database Design