• Use a variety of information-gathering techniques (e.g., interviews, facilitation, diagrams) to gather complex business data requirements from Business teams and data science and analytics teams.
• Collaborate with the team to research, evaluate and select the appropriate data sources.
• Serve as the business modeler/data analyst for data projects and initiatives, creating conceptual and logical business models used to generate physical data models and database schema.
• Document data model metadata such as data models, data definitions, data relationships/dependencies, data values, data lineage, data restrictions, data retention policies, data usage policies.
• Ensure project data model compliance with Enterprise Requirements such as definitions, regulations, privacy, quality, and governance during the design and implementation of database development, modeling and analysis projects
• Partner with DBAs/engineers to transform logical data models into physical database designs while optimizing the performance and maintainability of the physical database.
• Ensure that the database designs fulfill the requirements, including data volume, frequency needs, and long-term data growth.
• Understand business procedures, and develop a detailed knowledge of underlying data repositories and data products, including current and future uses of data, and creating and refining data models from requirements, business operations, and current systems.
• Leverage SQL and other technical skills to assist with tuning and delivering SQL queries for data management and data extraction.
• Transform business information into models by engaging with the business users and soliciting requirements and iteratively refining the conceptual, logical, and physical data models.

Skills: Business Analysis, Data Modeling, Documentation, Collaboration, SQL Proficiency, Regulatory Compliance, Performance Optimization, Data Source Evaluation

• Responsible for the development of enterprise data models at the conceptual and logical levels
• Identify and promote best practices and patterns for data modeling, and provide oversight activities related to data cleansing, data quality and data consolidation using standard data modeling methodologies and processes.
• Identifying opportunities for sharing and utilizing business data across program boundaries, thus extracting maximum benefit from the data resource.
• Collaborates with Data Administrators, Data Analysts, and development staff to develop and maintain the metadata architecture to maximize its use and increase the business's understanding of corporate data. 
• Design and implementation of an enterprise metadata maintenance and delivery application.
• Generate and maintain logical and physical data models for all phases of application development and data warehousing that adhere to industry best practices and corporate and industry standards.
• Provides input into the use of data models by the Enterprise BI and reporting tool to maximize the usefulness of corporate data structures by business users.
• Supports the collection and reporting of corporate metadata for development and business use.
• Promote sharing of corporate data, manage information as a resource, and continue efforts to prepare culture for the information management impacts of the continuous changes to business via data integration from a business perspective.
• Constantly reviewing and refining models as new requirements emerge
• Providing feedback to other Invicara teams on lessons learned using the Twinit platform

Skills: Enterprise Data Modeling, Best Practices Promotion, Data Utilization, Metadata Architecture Collaboration, Metadata Maintenance Application, Data Model Generation, BI Tool Support, Continuous Improvement

• Lead the design and implementation plan for the organization's Enterprise Data Warehousing solution.
• Work collaboratively with Solutions Architect to define Data Strategy for the business, including policies, principles, governance, etc.
• Seek clarifications and understand new product requirements from the Product functional team
• Translate product requirements to conceptual design from a database perspective
• Own design and development/enhancement of Data model and database objects
• Guide on technical solutions for product requirements and provide direction to development teams.
• Development and maintenance of Conceptual, Logical & Physical Data Models Conceptual/Logical Data Models and related data dictionary documentation
• Ensuring the proper data is available to achieve the business objectives for application development, analytical reporting and analysis. 
• Responsible for the development of enterprise data models at the conceptual, logical, and physical levels, be able to identify and promote best practices and patterns for data modeling
• Provide oversight activities related to data cleansing, data quality and data consolidation using standard data modeling methodologies and processes. 

Skills: Enterprise Data Warehousing, Data Strategy Collaboration, Requirements Clarification, Conceptual Design Translation, Data Model Ownership, Technical Guidance, Data Model Development, Data Quality Oversight

• Gather business requirements/listen to clients’ broad needs, and provide focus through facilitation of business design discussions
• Through a firm understanding of the business and design discussions, anticipate and provide value-added information through reporting
• Work with raw data and translate that into meaningful data models
• Create, maintain, and set standards for documentation on design, testing, and best practices
• Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
• Provide estimates on level of effort for all work to assist in business prioritization
• Conduct and document unit testing and support user acceptance testing
• Proactively evaluate opportunities for improvements and new technologies
• Review and validate data integrity, accuracy and completeness
• Monitoring and support of BI-related processes

Skills: Business Requirements Gathering, Value-Added Reporting, Data Translation, Documentation Standards, Naming Conventions Development, Effort Estimation, Testing Support, Data Integrity Review

• Translate business requirements into an Enterprise Data Warehouse (EDW) architecture, design and develop ETL and validate results with business representatives
• Support and enhance implemented BI solutions by monitoring and tuning queries and data loads, addressing user questions concerning data integrity, monitoring performance and communicating functional and technical issues
• Implement new business intelligence solutions and modify or configure existing deployed solutions
• Seek continuously and proactively to improve Business Intelligence services
• Maintain procedural and systems documentation for activities within the scope of this role
• Ensure the ongoing availability, reliability and performance of BI systems and operations to support business needs to agreed Service Levels.
• Actively and positively lead in project planning and execution activities pertaining to BI
• Develop and maintain automated test routines
• Provide strong BI 2nd / 3rd line support
• Actively share knowledge and experience with fellow team members
• Anticipates business client’s needs and proposes alternative business solutions.

Skills: EDW Architecture Translation, BI Solution Support, New BI Implementation, Continuous Improvement, Documentation Maintenance, BI System Reliability, Project Leadership, Knowledge Sharing

• Experience in creating Logical and Physical Data models and understanding of the Source systems in the Financial Services Domain.
• Experience in Relational Modeling, Dimensional Modeling and Modeling of Unstructured Data
• Ability to identify the client/market needs and propose impactful solutions
• Understanding of SDLC, data modeling and data management
• Adapt in Agile execution methodologies
• Participates in proof of concept executions, and architecture discussions and validates complex technical solution
• Experience with Lean / Agile development methodologies
• Experience in software development life cycle
• Experience in Project life cycle activities on creating Data Models
• Good understanding of the Source systems in the Banking and Financial Services domain and data architecture
• Good expertise in impact analysis due to changes or issues
• Experience in analyzing and translating business needs into long-term solution data models.
• Experience in evaluating existing data systems

Qualifications: BA in Computer Science with 4 years of Experience

• Experience in working with the development team to create conceptual data models and data flows.
• Experience in developing best practices for data coding to ensure consistency within the system.
• Experience in implementing data strategies and developing physical data models.
• Experience in updating and optimizing local and metadata models.
• Experience in evaluating implemented data systems for variances, discrepancies, and efficiency.
• Experience in troubleshooting and optimizing data systems
• Experience with Jira & Confluence
• Experience with migration projects from on-premise to cloud
• Ability to work in a team in diverse/ multiple stakeholder environment
• Verbal and written communication skills
• Experience and desire to work in a Global delivery environment

Qualifications: BS in Information Systems with 5 years of Experience

• Experience defining architectural designs and solutions for modernising legacy data layer to be cloud native
• Experience with defining ETL data pipelines to automate data movement from on-premises to the cloud
• Experience with Data Modelling for highly available applications especially utilising NO-SQL data stores
• Experience with legacy technology platforms especially Mainframe DB2
• Understanding of domain-driven design concept for defining bounded context and data layer as per Microservices-based Architecture
• Capability to interact with leadership and stakeholders to be able to define architectural designs for solutions
• Relational and Non-Relational databases in AWS cloud especially DynamoDB, S3, PostgreSQL, Aurora etc.
• AWS cloud services are preferred but not limited to Lambda, Kinesis, EC2, EMR, RDS, Redshift etc.
•  New and emerging data and analytics technologies (i.e. Hadoop, Spark, Elastic, AWS, etc.)
• Mainframe DB2, Batch Jobs, Stored Procedures and other Legacy Relational DBs

Qualifications: BA in Data Science with 6 years of Experience

• Experience in data modeling and administration experience advocating for data management principles and working in a team environment
• Knowledge of system development life cycles and methodologies
• Ability to handle multiple tasks and priorities
• Ability to collaborate with team members to meet project deadlines and milestones
• Experience in developing logical/physical models for operational systems, data warehouses and data marts.
• Experience in database administration and impact analysis of data structure changes.
• Expertise in ERWIN, OLTP, SQL, RUP, Oracle and MS Office Tools.
• Expertise in Relational and dimensional data modeling
• Experience in large-scale ODS or data warehouse environment
• Experience with one of the major data modeling tools (ER Studio or Erwin)
• Knowledge of relational databases and relational database design
• Experience in big data technologies such as HIVE
• Knowledge of AWS in big data technology stack. S3, Athena, Amazon RDS, Redshift etc.

Qualifications: BS in Mathematics with 8 years of Experience

• Experience with various data modeling techniques such as Relational, Dimensional, and Object models.
• Well-versed in various data warehouse delivery approaches such as Inmon, Kimball, Data Vault and others.
• Expert knowledge of data modeling tools such as Erwin, Information Architect or other similar ones. 
• Proficient in managing transitions across different data modeling layers to physical implementation (Conceptual - Logical - Physical - Actual implementation/DDLs)
• Experience with database features defined/configured at the physical model level, such as types of indexes, schemas, namespaces/tablespaces, etc.
• Proficient in maintaining, communicating and distributing data model releases to internal and external stakeholders.
• Experience collecting, discovering, managing, and disseminating data dictionaries, metadata and other data modeling-related artifacts.
• Knowledge of visualization tools requirements/constraints related to data structures.
• Understanding of ETL tools requirements/constraints related to data structures.
• Experience with Enterprise Systems (ERP, CRM...) data models, especially with cloud-based platforms such as Workday and Salesforce is a valuable asset.
• Exceptional written and oral communication skills, including the ability to present ideas and suggestions clearly and effectively.

Qualifications: BA in Statistics with 6 years of Experience