Lead Data Analyst

Data Discovery & Analysis

• Analyze all Netezza database tables to identify:
• Business-critical and frequently used tables
• Redundant and unused data assets
• Perform data profiling and quality analysis to understand structure, patterns, and anomalies
• Assess data dependencies and relationships across systems

Migration Assessment (Netezza → Azure)

• Evaluate and report:
• Number of tables already migrated to Azure
• Tables pending migration
• Validate data consistency between Netezza and Azure environments
• Support migration planning through impact analysis

Data Mapping & Lineage

• Create source-to-target data mapping documents
• Establish end-to-end data lineage across systems
• Document transformations and business rules applied during migration

Metadata & Documentation

• Develop and maintain:
• Metadata repository / definition documents
• Data dictionary / taxonomy (asset library)
• Table-level and column-level documentation
• Ensure alignment with enterprise data governance standards

Data Modeling

• Perform data modeling and mapping activities
• Create:
• Conceptual, logical, and physical data models
• Domain-based models for retail or business-specific datasets
• Design models optimized for:
• Analytical workloads
• Enterprise BI and reporting

Development & Implementation

• 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

Experience

• 4+ years of experience in data analysis, data modeling, or data engineering roles

Technical Skills

• Strong expertise in:
• SQL (mandatory)
• Python (or other scripting languages)
• Experience with:
• Netezza and cloud platforms (preferably Azure )
• Data modeling tools (e.g., ERwin, ER/Studio, Azure tools)
• Data warehousing and analytical workloads
• Solid understanding of:
• Data lineage and metadata management
• ETL/ELT processes
• Data migration strategies

Data Management Skills

• Data profiling and analysis techniques
• Data mapping and transformation documentation
• Metadata, taxonomy, and data dictionary creation •

Collaboration & Stakeholder Management

• Work closely with:
• Data engineers
• BI/reporting teams
• Data science teams
• Business stakeholders
• Gather and translate business requirements into technical data solutions
• Support downstream data marts, semantic layers, and analytics use cases