LATAM Sr. Data Validation Engineer - REMOTE

Insight Global; New York (NY); Remote; USD 120,000 - 160,000; Full time

Job summary

Insight Global seeks a Data Validation Engineer to join its QA Automation organization as a subject matter expert for data quality and validation. You will validate large-scale datasets, analytics platforms, and ETL pipelines supporting Paramount's streaming and digital products.

The role emphasizes Python and SQL proficiency, hands-on BigQuery experience, and collaboration with Data Engineers and business stakeholders to ensure trusted data for reporting and testing.

Qualifications

• 5+ years in Data Validation, Data Quality, Big Data QA, ETL Testing or related field.
• Strong Python development and writing code from scratch.
• Advanced SQL skills with complex queries.
• Experience validating large-scale datasets.
• Experience testing ETL/ELT data pipelines.
• Hands-on experience with BigQuery.
• Experience performing source-to-target data reconciliation.
• Experience troubleshooting data discrepancies and root-cause analysis.
• Understanding data quality principles: accuracy, completeness, consistency, integrity, duplicate detection.
• Experience in GCP or AWS cloud data environments.
• Experience with reporting tools.
• Experience leveraging AI/LLM tools to improve data validation/analysis/engineering workflows.
• Experience creating/enhancing validation logic with AI-assisted approaches.

Responsibilities

• Own end-to-end data validation across large-scale data pipelines and analytics platforms.
• Validate data movement through ETL/ELT processes and identify discrepancies between source and target systems.
• Develop Python-based data validation, reconciliation, and quality-check scripts.
• Write SQL queries to analyze data, investigate issues, and verify business logic.
• Perform source-to-target validation across BigQuery and cloud data platforms.
• Troubleshoot data quality issues and perform root cause analysis.
• Leverage AI/LLM technologies to generate/optimize validation rules, SQL queries, reconciliation logic, and analysis summaries.
• Collaborate with QA Automation Engineers to ensure trusted data for downstream testing efforts.
• Support validation of analytics across web, mobile, and connected TV platforms.
• Work in Agile teams using Jira and Confluence.

Skills

Python

SQL

BigQuery

ETL/ELT

Data Validation

AI/LLM

Cloud Data Environments

Data Quality

Tools

Python

SQL

BigQuery

Job description

Job Description

Insight Global is seeking a Data Validation Engineer for an end client to join its QA Automation organization and serve as the team's subject matter expert for data quality and validation. This individual will be responsible for validating large-scale datasets, analytics platforms, and ETL pipelines that support Paramount's streaming and digital products. The ideal candidate will have strong Python and SQL skills, experience working with BigQuery and cloud-based data environments, and a proven background validating data accuracy, completeness, and consistency. This role will also leverage AI tools and large language models (LLMs) to enhance data validation processes, automate analysis, improve anomaly detection, and accelerate root cause investigation. The Data Validation Engineer will partner closely with QA Automation Engineers, Data Engineers, and business stakeholders to ensure trusted data is available for reporting, analytics, and downstream testing efforts.

Responsibilities

• Own end-to-end data validation efforts across large-scale data pipelines and analytics platforms
• Validate data movement through ETL/ELT processes and identify discrepancies between source and target systems
• Develop and maintain Python-based data validation, reconciliation, and quality-checking scripts
• Write SQL queries to analyze data, investigate issues, and verify business logic
• Perform source-to-target validation across BigQuery and cloud-based data platforms
• Troubleshoot data quality issues and perform root cause analysis
• Leverage AI/LLM technologies (Claude, ChatGPT, Copilot, etc.) to generate and optimize validation rules, SQL queries, reconciliation logic, and analysis summaries
• Utilize AI-assisted techniques for anomaly detection, trend analysis, and identification of data inconsistencies
• Partner with QA Automation Engineers to ensure reliable, trusted data is available for downstream testing efforts
• Support validation of analytics generated across web, mobile, and connected TV (CTV) platforms
• Collaborate within Agile teams using Jira and Confluence

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 5+ years of experience in Data Validation, Data Quality, Big Data QA, ETL Testing, or a related field
• Strong Python development and writing code from scratch
• Advanced SQL skills with hands-on experience writing complex queries
• Experience validating large-scale datasets
• Experience testing ETL/ELT data pipelines
• Hands-on experience with BigQuery
• Experience performing source-to-target data reconciliation
• Experience troubleshooting data discrepancies and conducting root cause analysis
• Strong understanding of data quality principles, including:
  • oData accuracy
  • oData completeness
  • oData consistency
  • oData integrity
  • oDuplicate detection
• Experience working within GCP or AWS cloud data environments
• Experience with reporting tools
• Experience leveraging AI/LLM tools to improve data validation, analysis, or engineering workflows
• Experience creating or enhancing validation logic, reconciliation processes, or data quality checks using AI-assisted approaches