Data Business Analyst - PL/SQL, T-SQL & Data Warehousing

Data Business Analyst - PL/SQL, T-SQL & Data Warehousing

Location

Toronto, ON

Work Arrangement

Hybrid (2 days per week in-person at Toronto office preferred)

Years of Experience

8–10 years

Skills

Business Analysis, Solution and Functional Architect (SAFA), Data Analytics & Insights – ignio AIOps

Job Responsibilities

1. Analysis of Legacy Systems

• For each use case, analyze the mapping document of target tables to determine operational objectives by studying business functions, gathering information, and evaluating output requirements.
• Track the target field mapping back to the original data element in the source system.
• Strong knowledge of SQL to perform data analysis and data profiling on different legacy systems.
• Document the existing source-to-target data flow for each table, including:
• Business transformation rules applied.
• Key-cutting implemented to identify surrogate keys defined as unique identifiers in a table.
• Reference data used to enhance the context and validity of target data elements.
• For tables where mapping documentation is not available, TSBI and ETL leads must jointly review the code to extract business rules and capture them in the requirements document.

2. L2/L3 Model

• The business team is responsible for the creation of the L2 Model, supported by the Project Business Analyst, Solution Architect, and TSBI.
• Collaborate with data scientists, business analysts, and IT teams to integrate advanced L2/L3 models into the data pipeline.

3. Mapping Design of New L2/L3

• Prepare technical design and mapping (Data Movement Model) for the new L2 Model by working with Project Business Analysts and Solution Architects.
• Review the key-cutting process to be implemented on the L2 model and obtain approval from L2 Schema Owners.
• Only BORT system data will be populated into the L2 schema; other reference and tactical data will be directly consumed by L3 processes.
• L2-to-L3 mapping will contain business transformation rules for each target table.
• A custom surrogate key process will be implemented on L3 tables, which will contain different keys than L2 tables.
• Any system with one-off tables holding business data will be loaded into the L3 schema for target table processing.
• Spearhead the implementation of robust data governance policies and procedures, ensuring compliance with industry regulations and standards, resulting in a 20% reduction in data security incidents.
• Collaborate with cross-functional teams to design and implement data quality frameworks, improving data accuracy and integrity while reducing errors.

Role and Responsibilities

• Determine operational objectives by studying business functions, gathering information, and evaluating output requirements and formats.
• Design solutions, analyze requirements, and design modifications.
• Define project requirements by identifying project milestones, phases, and elements, and forming project teams.
• Monitor project progress by tracking activities, resolving problems, publishing progress reports, and recommending actions.
• Provide references for users by writing and maintaining mapping documentation.
• Maintain user confidence and protect operations by keeping information confidential.
• Prepare technical design and mapping through data collection, analysis, and profiling.
• Maintain professional and technical knowledge through workshops and continuous learning.
• Work with business and technology teams to fulfill data requirements.
• Prepare data models and technical design documentation according to standards.
• Assess intake requests for new projects and change requests.
• Strong knowledge of SQL and analysis of data from different product systems.

5 Mandatory Must-Have Skills and Experience

• Strong PL/SQL and T-SQL development and query optimization skills.
• Experience in Data Modelling using industry-standard modeling tools, Gap Analysis, and MS Visio.
• Strong understanding of Data Warehousing concepts, ETL processes, and source-to-target data mapping.
• Proven experience conducting requirement-gathering sessions and stakeholder workshops across business and technology teams.
• Experience in data analysis, data profiling, legacy system analysis, and technical documentation within large-scale data initiatives.

5 Nice-to-Have Skills and Experience

• Knowledge of banking domain data, including customer, account, and transaction data.
• Experience with Sybase PowerDesigner for data modeling.
• Knowledge of cloud technologies such as Amazon AWS.
• Familiarity with data governance and data quality frameworks.
• Experience supporting L2/L3 data models and enterprise data warehouse environments.