Ness Digital Engineering Careers

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

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