juicebox-migration-deep-dive

name	juicebox-migration-deep-dive
description	Advanced Juicebox data migration strategies. Use when migrating from other recruiting platforms, performing bulk data imports, or implementing complex data transformation pipelines. Trigger with phrases like "juicebox data migration", "migrate to juicebox", "juicebox import", "juicebox bulk migration".
allowed-tools	Read, Write, Edit, Bash(kubectl:*), Bash(curl:*)
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>

Juicebox Migration Deep Dive

Overview

Advanced strategies for migrating data to Juicebox from other recruiting and people search platforms.

Prerequisites

• Source data access and export capabilities
• Juicebox Enterprise plan (for bulk imports)
• Data mapping documentation
• Testing environment

Migration Sources

Source	Complexity	Common Issues
LinkedIn Recruiter	Medium	Rate limits, field mapping
Greenhouse	Low	Well-documented API
Lever	Low	Standard export format
Custom ATS	High	Custom transformation needed
CSV/Excel	Low	Data quality issues

Instructions

Step 1: Data Assessment

// scripts/assess-source-data.ts
interface DataAssessment {
  totalRecords: number;
  uniqueProfiles: number;
  duplicates: number;
  fieldCoverage: Record<string, number>;
  dataQualityScore: number;
  estimatedMigrationTime: string;
}

export async function assessSourceData(
  source: string,
  sampleSize: number = 1000
): Promise<DataAssessment> {
  const sample = await loadSampleData(source, sampleSize);

  const assessment: DataAssessment = {
    totalRecords: sample.total,
    uniqueProfiles: new Set(sample.records.map(r => r.email)).size,
    duplicates: sample.total - new Set(sample.records.map( => r.)).,
    : (sample.),
    : (sample.),
    : (sample.)
  };

   assessment;
}

 (): <, > {
   fields = [, , , , , ];
   : <, > = {};

   ( field  fields) {
     count = records.( r[field] && r[field].()).;
    coverage[field] = (count / records.) * ;
  }

   coverage;
}

Step 2: Schema Mapping

// lib/migration/schema-mapper.ts
export interface FieldMapping {
  sourceField: string;
  targetField: string;
  transform?: (value: any) => any;
  required: boolean;
}

export const linkedInMapping: FieldMapping[] = [
  { sourceField: 'firstName', targetField: 'first_name', required: true },
  { sourceField: 'lastName', targetField: 'last_name', required: true },
  {
    sourceField: 'fullName',
    targetField: 'name',
    transform: (v) => v || undefined,
    required: false
  },
  { sourceField: 'headline', targetField: 'title', required: false },
  { sourceField: 'companyName', targetField: 'company', required: false },
  {
    : ,
    : ,
    : normalizeLocation,
    : 
  },
  {
    : ,
    : ,
    : normalizeLinkedInUrl,
    : 
  },
  {
    : ,
    : ,
    : 
  }
];

   {
  () {}

  (: <, >): <, > {
     : <, > = {};

     ( mapping  .) {
       value = .(source, mapping.);

       (mapping.) {
        value = mapping.(value);
      }

       (value !==  && value !==  && value !== ) {
        .(target, mapping., value);
      }   (mapping.) {
          ();
      }
    }

     target;
  }
}

Step 3: Data Transformation Pipeline

// lib/migration/pipeline.ts
import { Transform, pipeline } from 'stream';
import { promisify } from 'util';

const pipelineAsync = promisify(pipeline);

export class MigrationPipeline {
  private stages: Transform[] = [];

  addStage(name: string, transform: (record: any) => any): this {
    this.stages.push(new Transform({
      objectMode: true,
      transform(record, encoding, callback) {
        try {
          const result = transform(record);
          if (result) {
            this.push(result);
          }
          callback();
        } catch (error) {
          callback(error as Error);
        }
      }
    }));
    return this;
  }

  async run(: , : ): <> {
     stats =  ();

     statsTracker =  ({
      : ,
      () {
        stats.();
        .(record);
        ();
      }
    });

     (
      source,
      ....,
      statsTracker,
      destination
    );

     stats;
  }
}


 pipeline =  ()
  .(, parseCSVRecord)
  .(, validateRecord)
  .(, deduplicateRecord)
  .(, transformToJuiceboxSchema)
  .(, enrichWithMetadata);

Step 4: Bulk Import with Rate Limiting

// lib/migration/bulk-importer.ts
export class BulkImporter {
  private rateLimiter: RateLimiter;
  private batchSize: number;
  private maxConcurrent: number;

  constructor(options: {
    requestsPerSecond: number;
    batchSize: number;
    maxConcurrent: number;
  }) {
    this.rateLimiter = new RateLimiter(options.requestsPerSecond);
    this.batchSize = options.batchSize;
    this.maxConcurrent = options.maxConcurrent;
  }

  async import(records: Profile[]): Promise<ImportResult> {
    const result: ImportResult = {
      total: records.length,
      successful: 0,
      failed: 0,
      errors: []
    };

    // Split into batches
    const batches = chunk(records, this.);

    
     semaphore =  (.);

     .(batches.( (batch, index) => {
       semaphore.();
       {
         ..();
         batchResult =  .(batch);

        result. += batchResult.;
        result. += batchResult.;
        result..(...batchResult.);

        logger.(, {
          : batchResult.,
          : batchResult.
        });
      }  {
        semaphore.();
      }
    }));

     result;
  }

    (: []): <> {
     {
       response =  juiceboxClient..(batch);
       {
        : response. + response.,
        : response.,
        : response.
      };
    }  (error) {
       {
        : ,
        : batch.,
        : [{ : (error  )., : batch }]
      };
    }
  }
}

Step 5: Validation and Reconciliation

// lib/migration/validator.ts
export class MigrationValidator {
  async validateMigration(
    sourceCount: number,
    destinationQuery: string
  ): Promise<ValidationReport> {
    const report: ValidationReport = {
      sourceCount,
      destinationCount: 0,
      matchRate: 0,
      missingRecords: [],
      dataIntegrityIssues: []
    };

    // Count destination records
    const destResult = await juiceboxClient.search.people({
      query: destinationQuery,
      limit: 0
    });
    report.destinationCount = destResult.total;
    report.matchRate = (report.destinationCount / sourceCount) * 100;

    // Sample validation
    const sampleSize = Math.min(100, sourceCount);
    const sample = await this.getSampleFromSource(sampleSize);

    for (const record of sample) {
      const match = await .(record);
       (!match) {
        report..(record.);
      }  {
         issues = .(record, match);
         (issues. > ) {
          report..({
            : record.,
            issues
          });
        }
      }
    }

     report;
  }

   (: , : ): [] {
     : [] = [];
     criticalFields = [, , ];

     ( field  criticalFields) {
       (source[field] !== dest[field]) {
        issues.();
      }
    }

     issues;
  }
}

Step 6: Rollback Strategy

// lib/migration/rollback.ts
export class MigrationRollback {
  private checkpointFile: string;

  constructor(migrationId: string) {
    this.checkpointFile = `./checkpoints/${migrationId}.json`;
  }

  async saveCheckpoint(state: MigrationState): Promise<void> {
    await fs.writeFile(this.checkpointFile, JSON.stringify(state, null, 2));
  }

  async loadCheckpoint(): Promise<MigrationState | null> {
    try {
      const data = await fs.readFile(this.checkpointFile, 'utf-8');
      return JSON.parse(data);
    } catch {
      return null;
    }
  }

  async rollback(migrationId: string): <> {
     checkpoint =  .();
     (!checkpoint) {
        ();
    }

    
     deleted =  juiceboxClient..({
      : { migrationId }
    });

     {
      : deleted.,
      : checkpoint.
    };
  }
}

Migration Checklist

## Pre-Migration
- [ ] Source data exported and validated
- [ ] Field mapping documented
- [ ] Test migration on sample data
- [ ] Rollback plan documented
- [ ] Stakeholder sign-off

## During Migration
- [ ] Monitoring dashboards active
- [ ] Progress tracking enabled
- [ ] Error logging configured
- [ ] Checkpoint saves working

## Post-Migration
- [ ] Reconciliation complete
- [ ] Data integrity verified
- [ ] Source system archived
- [ ] Documentation updated
- [ ] Team training complete

Output

• Data assessment tools
• Schema mapping configuration
• Transformation pipeline
• Bulk import with rate limiting
• Validation and reconciliation

Resources

• Bulk Import Guide
• Data Format Specifications

Summary

This skill pack completes the enterprise-grade Juicebox integration toolkit.