Data Architect

The Data Architect will provide technical expertise in analysis, design, development, rollout and maintenance of enterprise data models and solutions

Provides 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.

Understands and leverages best fit technologies (e.g., cloud, Hadoop, NoSQL, etc.) and approaches to address business and environmental challenges

Provides data understanding and coordinate data related activities with other data management groups such as master data management, data governance and metadata management.

Leadership not only in the conventional sense, but also within a team 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.

• Understand and translate business needs into data models and data architecture supporting long-term solutions.
• Work with the Application Development team to implement data strategies, build data flows and development of 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.
• Optimise 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.
• Organized and rigorous with versioning of documentation and models to ensure consistent delivery and understanding between the client and development team.
• 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.
• Lead 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, 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.

Education & Experience

• 6-8 years of Enterprise and Dimensional Data Modelling
• Experience using major data modelling tools (examples: Erwin, ER/Studio, PowerDesigner, etc.)
• 5+ years of experience architecting and building solutions on Databricks
• Experience with major database platforms (e.g. Oracle, SQL Server, Teradata, etc.)
• Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.)
• 3-5 years of management experience required
• 3-5 years consulting experience preferred
• Bachelor’s degree or equivalent experience, Master’s Degree Preferred
• Experience in data analysis and profiling
• Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Databricks, MySQL, Oracle, PostgreSQL, 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.
• Strong understanding of data integration best practices and concepts
• Strong data warehousing and OLTP systems from a modelling and integration perspective
• Strong understanding of data integration best practices and concepts
• Strong development experience under Unix and/or Windows environments
• Strong SQL skills required scripting (e.g., PL/SQL) preferred
• Strong Knowledge of all phases of the system development life cycle
• Understanding of modern data warehouse capabilities and technologies such as real-time, cloud, Big Data.
• Understanding of on premises and cloud infrastructure architectures (e.g. Azure, AWS, Google Cloud)

Preferred Skills & Experience

• Involved in documenting user requirements, business process and translation of business process into technical documents.
• Created Data Architect designs/documents for business processing requirements.
• Prepared Business Matrix diagram to identify business processes, dimensions, facts, conformed dimensions, junk and degenerate dimensions.
• 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 & logical data model.
• Assisted in process model development, identifying business process needs and requirements and modeling into useable, business-driven data processes.
• Redefined many attributes and relationships in the reverse engineered model and cleansed unwanted table/columns as part of data analysis responsibility.
• 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.
• Involved in developing SQL queries for extracting data from test and production databases to perform data analysis and data quality checks.
• 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.
• Analyzed, documented, and articulated the customer's current data warehouse/data mart architecture.
• 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 environment.
• 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.
• Design Functional Testing Standard Operating Procedures.
• Developed and optimized database structures, stored procedures, dynamic management views, DDL triggers, cursors, and user defined functions
• Can create documentation and presentations such that they “stands on their own.”
• Demonstrates ability to create new and innovative solutions to problems that have previously not been encountered.
• Ability to work independently on projects as well as collaborate effectively across teams
• Must excel in a fast-paced, agile environment where critical thinking and strong problem-solving skills are required for success
• Strong team building, interpersonal, analytical, problem identification and resolution skills
• Experience working with multi-level business communities
• Can effectively utilize SQL and/or available BI tool to validate/elaborate business rules.
• Demonstrates an understanding of EDM architectures and applies this knowledge in collaborating with the team to design effective solutions to business problems/issues.
• Understands and leverages a multi-layer semantic model to ensure scalability, durability, and supportability of the analytic solution.
• Understands modern data warehouse concepts (real-time, cloud, Big Data) and how to enable such capabilities from a reporting and analytic stand-point.
• Demonstrated ability to serve as a trusted advisor that builds influence with client management beyond simply EDM