BSA TSB

Apptoza Inc.; Toronto; Hybrid; CAD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Apptoza Inc. is seeking a skilled Data Analyst/Architect to analyze legacy systems, design L2/L3 data models, and ensure accurate data lineage from source to target.

You will map target tables, define transformation rules, and collaborate with TSBI, ETL leads, and data scientists. The role emphasizes strong SQL proficiency, data profiling, and documentation, with a focus on building robust data governance and quality frameworks across large-scale data initiatives in a hybrid Toronto office

Qualifications

• 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.

Responsibilities

• Analyze legacy systems and document target-table mappings to support operational objectives.
• Track mapping back to original data elements in source systems and capture business rules.
• Collaborate with data scientists, analysts, and IT to integrate L2/L3 models into the data pipeline.
• Prepare technical design and data movement mappings for new L2 models with architects and analysts.
• Review and approve key-cutting processes for L2 schema and ensure L3 data consumption is correct.
• Lead data governance efforts to reduce security incidents and improve data quality across projects.

Job description

Toronto, ON Hybrid (4 days per week in-person at Toronto office preferred)

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

Years Experience: 8-10

Job Responsibilities:

Analyze of Legacy System

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.

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.

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.