Data Analyst II

Compunnel

$90K — $120K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 2+ years in data engineering or ETL development
  • Strong SQL skills, preferably with Databricks/Spark SQL
  • Experience in building or maintaining ETL/data pipelines
  • Proficient with JSON, XML, CSV, and other flat-file formats
  • In-depth knowledge of data transformation and schema mapping
  • Experience troubleshooting production data pipelines
  • Strong analytical and problem-solving capabilities
  • Ability to manage multiple projects at once

Responsibilities

  • Build and maintain ETL pipelines for merchant onboarding
  • Analyze and transform merchant data feeds into standardized schemas
  • Develop SQL transformations in Databricks
  • Create and maintain mapping logic and transformation rules
  • Validate data quality and accuracy across pipelines
  • Investigate and resolve production issues with root cause analysis
  • Collaborate with cross-functional teams to onboard new merchants
  • Document transformation logic and mapping specifications
  • Identify automation opportunities for pipeline reliability

Benefits

  • Collaborative work environment with cross-functional teams
  • Opportunity to work on diverse and large datasets
  • Exposure to advanced data engineering tools and technologies
  • Support for professional development and skill enhancement
  • Engagement in challenging and impactful projects
Full Job Description
Job Summary

The Data Analyst is responsible for supporting merchant data onboarding and pipeline maintenance by building, validating, and troubleshooting ETL/data pipelines. This role ensures accurate ingestion of merchant data feeds into downstream systems through schema mapping, transformations, and production troubleshooting. The ideal candidate is skilled in SQL, ETL development, and working with large datasets across multiple formats

Key Responsibilities

  1. Build and maintain ETL pipelines to support merchant onboarding and integrations
  2. Analyze merchant data feeds (JSON, XML, CSV, TXT) and transform them into standardized schemas
  3. Develop SQL transformations in Databricks (Spark SQL preferred)
  4. Create and maintain mapping logic and transformation rules
  5. Validate data quality, completeness, and accuracy across ingestion pipelines
  6. Investigate and resolve issues including root cause analysis and remediation
  7. Collaborate with cross-functional teams (Technical Account Managers, Product, Engineering) to onboard new merchants
  8. Support multiple implementations while meeting delivery timelines
  9. Document transformation logic, mapping specifications, and operational procedures
  10. Identify automation opportunities to improve pipeline reliability

Required Qualifications

  • 2+ years of experience in data engineering, ETL development, or data integration
  • Strong SQL skills (Databricks/Spark SQL preferred)
  • Experience building or maintaining ETL/data pipelines
  • Experience working with JSON, XML, CSV and other flat-file formats
  • Strong understanding of data transformation, schema mapping, and validation
  • Experience troubleshooting production data pipelines
  • Strong analytical and problem-solving skills
  • Ability to manage multiple projects simultaneously

Preferred Qualifications

  1. Experience with Databricks
  2. Experience integrating third-party or merchant data feeds
  3. Experience supporting production systems and on-call troubleshooting

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