juicebox-migration-deep-dive

jeremylongshore's avatarfrom jeremylongshore

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".

939stars🔀114forks📁View on GitHub🕐Updated Jan 11, 2026

When & Why to Use This Skill

This Claude skill provides a comprehensive, enterprise-grade framework for migrating recruiting data to the Juicebox platform. It automates the end-to-end migration lifecycle—including data assessment, schema mapping, transformation pipelines, and bulk imports—enabling seamless transitions from platforms like LinkedIn Recruiter, Greenhouse, and Lever while ensuring maximum data integrity.

Use Cases

  • Migrating candidate databases from legacy ATS platforms (e.g., Greenhouse, Lever) to Juicebox with automated field mapping.
  • Executing high-volume bulk imports of talent profiles from LinkedIn Recruiter while managing API rate limits and concurrency.
  • Building custom data transformation pipelines to normalize and clean inconsistent recruiting data before system ingestion.
  • Performing post-migration validation and reconciliation to ensure data accuracy and identify missing records.
  • Implementing rollback strategies and checkpoints to maintain data safety during complex, multi-stage migration projects.
namejuicebox-migration-deep-dive
description|
allowed-toolsRead, Write, Edit, Bash(kubectl:*), Bash(curl:*)
version1.0.0
licenseMIT
authorJeremy Longshore <jeremy@intentsolutions.io>

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 => r.email)).size,
    fieldCoverage: calculateFieldCoverage(sample.records),
    dataQualityScore: calculateQualityScore(sample.records),
    estimatedMigrationTime: estimateMigrationTime(sample.total)
  };

  return assessment;
}

function calculateFieldCoverage(records: any[]): Record<string, number> {
  const fields = ['name', 'email', 'title', 'company', 'location', 'phone'];
  const coverage: Record<string, number> = {};

  for (const field of fields) {
    const count = records.filter(r => r[field] && r[field].trim()).length;
    coverage[field] = (count / records.length) * 100;
  }

  return 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 },
  {
    sourceField: 'location',
    targetField: 'location',
    transform: normalizeLocation,
    required: false
  },
  {
    sourceField: 'profileUrl',
    targetField: 'linkedin_url',
    transform: normalizeLinkedInUrl,
    required: false
  },
  {
    sourceField: 'connectionDegree',
    targetField: 'metadata.connection_degree',
    required: false
  }
];

export class SchemaMapper {
  constructor(private mappings: FieldMapping[]) {}

  mapRecord(source: Record<string, any>): Record<string, any> {
    const target: Record<string, any> = {};

    for (const mapping of this.mappings) {
      let value = this.getNestedValue(source, mapping.sourceField);

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

      if (value !== undefined && value !== null && value !== '') {
        this.setNestedValue(target, mapping.targetField, value);
      } else if (mapping.required) {
        throw new Error(`Required field missing: ${mapping.sourceField}`);
      }
    }

    return 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(source: Readable, destination: Writable): Promise<MigrationStats> {
    const stats = new MigrationStats();

    const statsTracker = new Transform({
      objectMode: true,
      transform(record, encoding, callback) {
        stats.increment();
        this.push(record);
        callback();
      }
    });

    await pipelineAsync(
      source,
      ...this.stages,
      statsTracker,
      destination
    );

    return stats;
  }
}

// Usage
const pipeline = new MigrationPipeline()
  .addStage('parse', parseCSVRecord)
  .addStage('validate', validateRecord)
  .addStage('deduplicate', deduplicateRecord)
  .addStage('transform', transformToJuiceboxSchema)
  .addStage('enrich', 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.batchSize);

    // Process batches with concurrency limit
    const semaphore = new Semaphore(this.maxConcurrent);

    await Promise.all(batches.map(async (batch, index) => {
      await semaphore.acquire();
      try {
        await this.rateLimiter.wait();
        const batchResult = await this.importBatch(batch);

        result.successful += batchResult.successful;
        result.failed += batchResult.failed;
        result.errors.push(...batchResult.errors);

        logger.info(`Batch ${index + 1}/${batches.length} complete`, {
          successful: batchResult.successful,
          failed: batchResult.failed
        });
      } finally {
        semaphore.release();
      }
    }));

    return result;
  }

  private async importBatch(batch: Profile[]): Promise<BatchResult> {
    try {
      const response = await juiceboxClient.profiles.bulkImport(batch);
      return {
        successful: response.created + response.updated,
        failed: response.failed,
        errors: response.errors
      };
    } catch (error) {
      return {
        successful: 0,
        failed: batch.length,
        errors: [{ message: (error as Error).message, records: 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 this.findInDestination(record);
      if (!match) {
        report.missingRecords.push(record.id);
      } else {
        const issues = this.compareRecords(record, match);
        if (issues.length > 0) {
          report.dataIntegrityIssues.push({
            recordId: record.id,
            issues
          });
        }
      }
    }

    return report;
  }

  private compareRecords(source: any, dest: any): string[] {
    const issues: string[] = [];
    const criticalFields = ['name', 'email', 'company'];

    for (const field of criticalFields) {
      if (source[field] !== dest[field]) {
        issues.push(`${field} mismatch: "${source[field]}" vs "${dest[field]}"`);
      }
    }

    return 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): Promise<RollbackResult> {
    const checkpoint = await this.loadCheckpoint();
    if (!checkpoint) {
      throw new Error('No checkpoint found for rollback');
    }

    // Delete imported records
    const deleted = await juiceboxClient.profiles.bulkDelete({
      filter: { migrationId }
    });

    return {
      recordsRolledBack: deleted.count,
      checkpoint: checkpoint.lastProcessedId
    };
  }
}

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

Summary

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