QA Automation Engineer - Data

About Dynatron

Dynatron is transforming the automotive service industry with intelligent SaaS solutions that deliver measurable results for thousands of dealership service departments. Our proprietary analytics, automation capabilities, and AI-powered workflows empower service leaders to increase profitability, elevate customer satisfaction, and operate with greater efficiency. With accelerating demand and a rapidly expanding product ecosystem, we’re scaling fast, and we’re just getting started.

The Opportunity

We’re seeking a highly skilled and detail-oriented QA Automation Engineer to lead automated and manual testing efforts across our growing analytics and data engineering ecosystem. In this role, you’ll validate large-scale data workflows, strengthen data quality, and ensure the reliability of data moving across complex ETL/ELT pipelines. Your work will directly support the accuracy, consistency, and performance of mission-critical data systems used across Dynatron’s products and operations.

This position is ideal for an engineer with deep experience in data-centric QA automation, strong analytical thinking, and a passion for building scalable, reusable testing frameworks that guarantee our data is trustworthy, consistent, and ready for analytics and AI-driven innovation.

Important Information - Please Read

Application & Interview Process

To be considered for this role, applicants must complete the following steps:

1. Submit an application through the company website, including a resume.
2. Record a minimum 60-second introduction using Vocaroo (https://vocaroo.com/) and paste the URL into the application.
3. Participate in an online Screening Interview, scheduled between 8:00 AM - 2:00 PM Eastern Time (USA).
4. Participate in Round 1 Video Interview within the same time window.
5. Complete a technical assessment; successful candidates may be asked to discuss their solution in a follow-up interview.
6. Participate in Round 2 Technical Interview, also between 8:00 AM - 2:00 PM Eastern Time (USA).

Hours of Collaboration

You must be available during core collaboration hours with the US team:

• 6:30 PM – 11:30 PM IST
• 9:00 AM – 2:00 PM EST (USA)
• 8:00 AM – 1:00 PM CST (USA)
• 7:00 AM – 12:00 PM MST (USA)
• 6:00 AM – 11:00 AM PST (USA)

An additional 3 flexible hours per day can be worked outside of core hours based on your preference.

What You’ll Do

Test Automation & Framework Development

• Design, develop, and maintain automated test frameworks for data pipelines and ETL workflows.
• Build reusable test components for Snowflake, Databricks, ADF, Airflow, streaming pipelines, and more.
• Automate schema validation, regression testing, backfill testing, and data contract checks.
• Implement automated monitors for stream quality, lag, CDC correctness, and consistency.

Data Quality & Validation

• Create, execute, and maintain detailed test cases, test plans, and regression suites for data enhancements.
• Validate data accuracy, completeness, and integrity across ingestion, transformation, and downstream layers.
• Develop SQL-based validation scripts to compare source vs. target datasets.
• Perform root-cause analysis for data inconsistencies and work closely with engineering teams to resolve issues.

Collaboration & Agile Delivery

• Partner with Data Engineers, Analysts, and Product teams to understand transformation logic and business rules.
• Participate in sprint ceremonies including requirement reviews, estimations, and deployment validations.
• Monitor pipeline execution, identify defects early, and verify fixes through structured retesting.

Quality Engineering Leadership

• Drive QA best practices across multiple data environments.
• Create documentation, reusable assets, and frameworks that elevate overall data quality discipline.

What You Bring

• 6-10+ years of QA Automation experience in data-intensive or analytics-driven environments.
• Strong proficiency in SQL for data validation, profiling, and regression testing.
• Hands-on experience with Python for automation scripting and data validation.
• Extensive experience testing ETL/ELT pipelines and cloud-based data workflows.
• Deep understanding of QA methodologies, test planning, defect lifecycle management, and automation principles.
• Experience with CI/CD pipelines, Git-based workflows, and automated execution environments.
• Strong analytical and troubleshooting skills for identifying data quality issues.
• Excellent written and verbal communication skills.
• Hands-on experience with Snowflake and at least one test automation framework/tool.

Preferred Qualifications

• Experience with Databricks, ADF, AWS Glue, BigQuery, Redshift, or similar data platforms.
• Exposure to streaming technologies such as Kafka, Kinesis, or Debezium.
• Familiarity with metadata & lineage tools and dbt tests.
• Experience with Airflow, dbt, Fivetran, or other orchestration platforms.
• Experience with Python-based automation frameworks (pytest, unittest, Behave).
• Hands-on familiarity with:
  • Selenium (workflow/UI triggers)
  • Postman/Insomnia (API testing)
  • JMeter/Locust (performance testing)
  • Robot Framework
  • Great Expectations or equivalent data quality frameworks
  • Jira/XRay, TestRail, or similar test management systems

Why Dynatron

• Work with a high-performance, globally distributed team shaping the future of data integrity and analytics quality.
• Build automation frameworks that directly influence the reliability and speed of our data product ecosystem.
• A remote-first environment with flexibility, autonomy, and strong cross-functional collaboration.
• Opportunity to support a fast-scaling SaaS company redefining the under-innovated automotive service industry.

If you thrive in data-driven environments, excel in automation, and want to make a measurable impact on product quality and engineering velocity, we’d love to meet you.