Lead Data Analyst

Ness Digital Engineering•Ontario, ON

11d

About The Position

The Lead Data Analyst will be responsible for analyzing Netezza database tables to identify critical, frequently used, redundant, and unused data assets. This role involves performing data profiling and quality analysis to understand data structure, patterns, and anomalies, as well as assessing data dependencies and relationships across systems. A key part of the role will be supporting the migration from Netezza to Azure by evaluating migration progress, validating data consistency, and performing impact analysis for planning. The Lead Data Analyst will also be responsible for creating source-to-target data mapping documents, establishing data lineage, and documenting transformations. Additionally, this position involves developing and maintaining metadata repositories, data dictionaries, and comprehensive documentation, ensuring alignment with enterprise data governance standards. Data modeling, including conceptual, logical, and physical models optimized for analytical workloads and enterprise BI, is also a core responsibility. The role requires developing and optimizing SQL queries, creating DDL scripts, performing data wrangling with Python, and working with various data sources. Collaboration with data engineers, BI/reporting teams, data science teams, and business stakeholders is essential to translate business requirements into technical data solutions.

Requirements

4+ years of experience in data analysis, data modeling, or data engineering roles
Strong expertise in SQL (mandatory)
Strong expertise in Python (or other scripting languages)
Experience with Netezza and cloud platforms (preferably Azure)
Experience with data modeling tools (e.g., ERwin, ER/Studio, Azure tools)
Experience with data warehousing and analytical workloads
Solid understanding of data lineage and metadata management
Solid understanding of ETL/ELT processes
Solid understanding of data migration strategies
Data profiling and analysis techniques
Data mapping and transformation documentation
Metadata, taxonomy, and data dictionary creation
Collaboration & Stakeholder Management

Responsibilities

Analyze all Netezza database tables to identify business-critical, frequently used, redundant, and unused data assets.
Perform data profiling and quality analysis to understand structure, patterns, and anomalies.
Assess data dependencies and relationships across systems.
Evaluate and report on the number of tables already migrated to Azure and tables pending migration.
Validate data consistency between Netezza and Azure environments.
Support migration planning through impact analysis.
Create source-to-target data mapping documents.
Establish end-to-end data lineage across systems.
Document transformations and business rules applied during migration.
Develop and maintain metadata repository / definition documents.
Develop and maintain data dictionary / taxonomy (asset library).
Develop and maintain table-level and column-level documentation.
Ensure alignment with enterprise data governance standards.
Perform data modeling and mapping activities.
Create conceptual, logical, and physical data models.
Create domain-based models for retail or business-specific datasets.
Design models optimized for analytical workloads and enterprise BI and reporting.
Write and optimize SQL queries for data analysis and validation.
Develop DDL scripts and assist in deploying data models across environments.
Perform data wrangling and transformation using Python or similar tools.
Work with data lakes and structured/unstructured data sources.
Work closely with data engineers, BI/reporting teams, data science teams, and business stakeholders.
Gather and translate business requirements into technical data solutions.
Support downstream data marts, semantic layers, and analytics use cases.