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 OpportunityWe’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 ReadBecause Dynatron does not have a physical office in India, this position will be structured as an Independent Contractor role.
- No taxes will be deducted by Dynatron (contractor is responsible for compliance)
- No health insurance or employee benefits are provided
- India Gazetted Holidays and 24 days of PTO are included as part of the contract
Application & Interview Process
To be considered for this role, applicants must complete the following steps:
- Submit an application through the company website, including a resume
- Record a minimum 60-second introduction using Vocaroo (https://vocaroo.com/) and paste the URL into the application
- Participate in an online Screening Interview, scheduled between 8:00 AM - 2:00 PM Eastern Time (USA)
- Participate in Round 1 Video Interview within the same time window
- Complete a technical assessment; successful candidates may be asked to discuss their solution in a follow-up interview
- 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 DoTest 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.
