About the role

Data Modeler

Job Summary

The data architect designs, implements, and documents data architecture and enterprise data modelling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, machine learning, data science, and other business interests.

The successful candidate will:

Provide technical expertise in needs identification, data modelling, data movement and transformation mapping (source to target), automation and testing strategies, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective.
Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively.
Exhibit leadership not only in the conventional sense, but also within a team where we expect people to be leaders. Candidate should elicit leadership qualities such as Innovation, Critical thinking, optimism/positivity, Communication, Time Management, Collaboration, Problem-solving, Acting Independently, Knowledge sharing and Approachable.

Essential Duties:

Understand and translate business needs into data models supporting long-term solutions.
Work with the Application Development team to implement data strategies, build data flows and develop conceptual data models.
Create and maintain conceptual, logical and physical data models using best practices to ensure high data quality and reduced redundancy, along with corresponding metadata.
Optimize and update logical and physical data models to support new and existing projects.
Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
Recommend opportunities for reuse of data models in new environments.
Perform reverse engineering of physical data models from databases and SQL scripts.
Evaluate data models and physical databases for variances and discrepancies.
Validate business data objects for accuracy and completeness.
Analyze data-related system integration challenges and propose appropriate solutions.
Develop data models according to company standards. Guide System Analysts, Engineers, Programmers and others on project limitations and capabilities, performance requirements and interfaces.
Review modifications to existing software to improve efficiency and performance.
Examine new application design and recommend corrections if required.
Assist with and support setting the data architecture direction (including data movement approach, architecture / technology strategy, and any other data-related considerations to ensure business value), ensuring data architecture deliverables are developed, ensuring compliance to standards and guidelines, implementing the data architecture, and supporting technical developers at a project or business unit level.
Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels.

Required Qualifications:

7-10 Years industry implementation experience with one or more data modelling tools such as Erwin, ERStudio, PowerDesigner etc.
Minimum of 8 years of data architecture, data modelling (Data Vault and Dimensional, 3NF) or similar experience
5-7 years of management experience required
5-7 years consulting experience preferred
Experience working with dimensionally modelled data
Bachelor’s degree or equivalent experience, Master’s Degree Preferred
Understanding of cloud (Azure, AWS, GCP, Snowflake preferred) and on premises architectures
Experience in data analysis and profiling
Strong data warehousing and OLTP systems from an integration perspective
Strong understanding of data integration best practices and concepts
Strong SQL skills required scripting preferred
Strong Knowledge of all phases of the system development life cycle
Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Databricks, MySQL, Oracle, PostgresSQL, Hadoop, Snowflake, etc.)
Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.)
Understanding of modern data warehouse capabilities and technologies such as real-time, cloud, Big Data.

Preferred Skills & Experience:

Involved in documenting user requirements, business processes and translation of business processes into technical documents.
Created Data Architect designs/documents for business processing requirements.
Analyzed and audited Requirements & Business Processes.
Prepared Business Matrix diagram to identify business processes, dimensions, facts, conformed dimensions, junk and degenerate dimensions.
Worked as a part of the review and collaboration sessions regarding business processes, canonical (BOM) modeling.
Profile the source system data to identify the business process and business requirement with operational system data.
Designed/captured the business processes & then mapped them to the conceptual data model.
Involved in modeling business processes through UML diagrams using Rational Rose.
Prepared Test Scenarios based on understanding of business process flow.
Assisted in process model development, identifying business process needs and requirements and modeling into usable, business-driven data processes.
Participate in requirement gathering, design review and code review meetings. Analyze business processes and optimize existing extract stored procedures.
Redefined many attributes and relationships in the reverse engineered model and cleansed unwanted table/columns as part of data analysis responsibility.
Reviewed Entities and relationships in the engineered model and cleansed unwanted tables/columns as part of data analysis responsibilities.
Conducted logical data analysis and data modeling joint application design (JAD) sessions, documented data-related standards.
Performed data analysis to support mapping and transformation of data from legacy systems to physical data models.
Gather accurate data by data analysis and functional analysis.
Conduct logical data modeling and data analysis.
Involved in developing SQL queries for extracting data from test and production databases to perform data analysis and data quality checks.
Worked with tools like TOAD for data analysis, SQL assistant, Tortoise SVN and red gate's SQL compare.
Developed robust and efficient oracle PL/SQL procedures, packages and functions that were useful for day to day data analysis.
Conducted data analysis on application views, functions and triggers, and tuned for performance, fixed missing/wrongly mapped data.
Involved in the data mapping, data analysis and Gap analysis between the Legacy systems and the Vendor Packages.
Performed Data Profiling and Data Analysis using SQL queries looking for Data issues, Data anomalies.
Defined Data architecture Strategy, Data Management Strategy, data standards, Data architectural.
Consolidated and generated database standards and naming conventions to enhance Enterprise Data Architecture processes.
Developed an activity centered data architecture and a process architecture for automated data extraction.
Analyzed, documented and articulated the customer's current data warehouse/data mart architecture.
Generated Logical Data Models for old databases using Reverse engineering and documented in order to implement Forward Engineering procedures.
Designed and implemented procedures for mapping interface data between legacy systems and a new implementation.
Revised and rewrote their design specifications, established internal procedures for product certification.
Designed standards and procedures to manage metadata in a structured and unstructured data environments.
Mentored existing staff on data administrative processes procedures and standards.
Created standards and procedures for metadata collection and repository maintenance.
Designed and developed several complex database procedures, packages.
Developed business specific custom reports using PL/SQL procedures.
Established auditing procedures to ensure data integrity.
Developed stored procedures to implement business logic.
Designed Functional Testing Standard Operating Procedures.
Worked with different teams to provide them with the essential stored procedures and packages and the required access to the data.
Developed and optimized database structures, stored procedures, dynamic management views, DDL triggers, cursors and user defined functions.