Teradata Migration Assessment & Discovery Engineer

Seeking hands-on Assessment & Discovery Engineers to analyze a complex Teradata ecosystem in preparation for migration to BigQuery. Candidates should combine strong legacy system analysis with coding/automation, quantitative analysis and stakeholder interaction.

Key Responsibilities

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  Inventory Teradata databases, tables, views, procedures, BTEQ scripts, loaders and ETL processes.

  
  


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  Analyze DBQL and metadata for query frequency, CPU, I/O, runtime, concurrency, object usage and application/user activity.

  
  


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  Perform volumetric analysis, including data volumes, table sizes, historical growth, processing volumes, workload distribution and peak patterns.

  
  


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  Analyze in-house ETL frameworks, BTEQ/load processes and embedded transformation logic.

  
  


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  Analyze Tivoli job streams, schedules, dependencies and critical batch chains.

  
  


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  Assess SSAS and Power BI dependencies and usage.

  
  


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  Build end-to-end lineage and dependency mappings.

  
  


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  Develop Python/SQL/Shell scripts and reusable utilities to speed up discovery and analysis rather than relying entirely on manual assessment.

  
  


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  Correlate DBQL, metadata, ETL, scheduler and BI findings to identify dependency gaps.

  
  


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  Produce meaningful statistics such as active vs inactive objects, workload utilization, query distribution, dependency counts, complexity and migration candidates.

  
  


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  Create analytical views, charts, heatmaps and summaries from large discovery datasets.

  
  


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  Coordinate with technical/application SMEs to validate findings and resolve undocumented dependencies.

  
  


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  Present findings and recommendations clearly to the Architect and program stakeholders.

  
  

Must-Have Skills

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  Teradata and strong SQL.

  
  


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  Teradata DBQL and metadata analysis.

  
  


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  BTEQ / Teradata loaders.

  
  


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  ETL and Data Warehousing.

  
  


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  Batch/job dependency analysis.

  
  


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  Python/Shell/SQL scripting and automation capability.

  
  


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  Data lineage and dependency analysis.

  
  


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  Strong quantitative/volumetric analysis skills.

  
  


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  Ability to interpret large datasets and derive meaningful insights.

  
  


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  Strong communication, stakeholder coordination and presentation skills.

  
  

Preferred Skills

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  Tivoli Workload Scheduler.

  
  


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  Power BI / SSAS.

  
  


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  BigQuery / GCP exposure.

  
  


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  Experience creating discovery tools, scripts or assessment accelerators.

  
  


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  Automated SQL/BTEQ parsing or metadata analysis.

  
  


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  Dashboarding/data visualization skills.

  
  


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  Exposure to AI/GenAI or agent-based approaches for accelerating assessment, code analysis or dependency discovery.