Data Modeler / Analyst Lead - Minneapolis, MN - ASCII Group

Work with business users to obtain data requirements and analyze source systems data.Design and develop conceptual, logical and physical data models for the operational and analytical data modelsWork closely with the technical and application architects, and developers to implement the data architecture and application solutionCommunicate physical database designs to, and work with, database administrator to implement databasesDocument data flows, identify appropriate data sources, entities, relationships and redundancies.Manage data integrity and data quality.Maintain technical & business metadata. Generate metadata for Hadoop ingestion for different ingestion frameworks. Design data structures and document data meanings, definitions and intended use, work with various departments/leaders and data stewards to make the "metadata” available.Define and document the data architecture for operational databases, reporting and provisioning platforms, including the physical components and their functionalitySupport data strategies, standards, guidelines data quality process and governance across the enterpriseProvide leadership in researching and architecting emerging technology solutions to meet business strategies and objectives. Do you have the skills that will enable you to succeed in this role? Wed love to work with you if you have: Relational and dimensional data modeling and database design, Erwin (Data modeling) skills. Strong SQL, Python and some spark knowledge. Hands on Hive (Hadoop) experience. Knowledge of data architectural approaches, patterns and emerging technologies (RDBMS, Hadoop and Cloud)Exposure and knowledge of Cloud platforms, cloud architecture, capabilities and processes like GCP, Azure is great asset.Ability to translate business needs into technical solutions. Strong Analytical skills.Experience creating architecture and strategy artifactsExperience of XML, JSON, Copybook, CSV files ingestion Experience working in Agile environmentKnowledge of Data Governance process for metadata and lineage management is strong asset. Exposure to any Data Governance tools like IGC, Collibra is an asset. Domain Knowledge in financial Services and enterprise functions is strong asset.Knowledge of database administration, database performance tuning, source & target data structures, ETL processes & products.