Job description
Data Modeler
- SQL, ETL & DWH Location: Toronto Office Work Model: Hybrid – 2 days per week in office Experience Required: 6-8 Years Skills:
- Data Concepts & Data Modelling
- Data Warehouse
- MySQL MUST HAVE Skills/Experience:
- Strong knowledge PL SQL/T-SQL
- Experience in Data Modelling (Any designer tool), Gap Analysis, and MS Visio
- Good understanding of Data Warehousing concepts and ETL Process
- Ability to drive requirement sessions/meetings with various stakeholders NICE TO HAVE Skills/Experience:
- Knowledge in Banking domains, including regular account, customer data, and transaction data in various banking business processes
- Sybase Power Designer for data modeling
- Knowledge in Cloud Technologies, such as Amazon AWS Role and Responsibilities:
- Determines operational objectives by studying business functions, gathering information, and evaluating output requirements and formats.
- Designs, analyzes requirements, and designs modifications.
- Defines project requirements by identifying project milestones, phases, and elements, forming project teams.
- Monitors project progress by tracking activity, resolving problems, publishing progress reports, and recommending actions.
- Provides references for users by writing and maintaining mapping documentation.
- Maintains user confidence and protects operations by keeping information confidential.
- Prepares technical design and mapping by collecting, analyzing, and data profiling.
- Maintains professional and technical knowledge by attending workshops.
- Works with business and technology teams to fulfill their data needs.
- Performs Data Modelling and prepares technical design documentation as per standards.
- Assesses intake requests for new projects and change requests.
- Strong knowledge in SQL and analysis of data from different product systems. Detailed Breakdown: Analyze Legacy System:
- Analyze the mapping document of target tables to determine operational objectives by studying business functions, gathering information, and evaluating output requirements.
- Track target field mapping back to origin data elements in the source system.
- Perform data analysis and data profiling on different legacy systems using strong SQL knowledge.
- Document 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 documents are not available, TSBI and ETL leads must review the code to extract business rules applied and capture them into the requirement document. L2/L3 Model:
- Business team would be responsible for the creation of L2 Model supported by 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 Architect.
- Review the Key Cutting process to be implemented on the L2 model and get approval from L2 Schema Owners.
- Only BORT System data would be populated into L2 schema; other reference and tactical data would directly be consumed by L3 processes.
- L2 to L3 mapping would contain business transformation rules for each target table.
- Custom Surrogate Key process would be implemented on L3 tables, which would contain different keys than L2 tables.
- Any system having one-off tables holding business data would be loaded into L3 schema for target table processing.
- Spearheaded the implementation of robust data governance policies and procedures, ensuring compliance with industry regulations and standards.
- Collaborate with cross-functional teams to design and implement data quality frameworks, improving data accuracy and integrity, and reducing errors.