Data Analyst

About the job
Data Analyst

Location: Toronto (Hybrid)

Data Discovery & Analy

sisAnalyze all Netezza database tables to identi
fy:Business-critical and frequently used tab
lesRedundant and unused data ass
etsPerform data profiling and quality analysis to understand structure, patterns, and anomal
iesAssess data dependencies and relationships across syst
emsMigration Assessment (Netezza → Azu

re)Evaluate and repo
rt:Number of tables already migrated to Az
ureTables pending migrat
ionValidate data consistency between Netezza and Azure environme
ntsSupport migration planning through impact analy
sisData Mapping & Line

ageCreate source-to-target data mapping docume
ntsEstablish end-to-end data lineage across syst
emsDocument transformations and business rules applied during migrat
ionMetadata & Documentat

ionDevelop and mainta
in:Metadata repository / definition docume
ntsData dictionary / taxonomy (asset libra
ry)Table-level and column-level documentat
ionEnsure alignment with enterprise data governance standa
rdsData Model

ingPerform data modeling and mapping activit
iesCrea
te:Conceptual, logical, and physical data mod
elsDomain-based models for retail or business-specific datas
etsDesign models optimized f
or:Analytical worklo
adsEnterprise BI and report
ingDevelopment & Implementat

ionWrite and optimize SQL queries for data analysis and validat
ionDevelop DDL scripts and assist in deploying data models across environme
ntsPerform data wrangling and transformation using Python or similar to
olsWork with data lakes and structured/unstructured data sour
cesExperie

nce4+ years of experience in data analysis, data modeling, or data engineering ro
lesTechnical Ski

llsStrong expertise
in:SQL (mandato
ry)Python (or other scripting languag
es)Experience wi
th:Netezza and cloud platforms (preferably Azu
re)Data modeling tools (e.g., ERwin, ER/Studio, Azure too
ls)Data warehousing and analytical worklo
adsSolid understanding
of:Data lineage and metadata managem
entETL/ELT proces
sesData migration strateg
iesData Management Ski

llsData profiling and analysis techniq
uesData mapping and transformation documentat
ionMetadata, taxonomy, and data dictionary creat
ionCollaboration & Stakeholder Managem
entWork closely wi
th:Data engine
ersBI/reporting te
amsData science te
amsBusiness stakehold
ersGather and translate business requirements into technical data soluti
onsSupport downstream data marts, semantic layers, and analytics use ca

ses