Data QA

Velvetech is an American global software development company headquartered in Miami, FL, and with an office in Chicago, IL. Velvetech has its developers strategically distributed in 10+ global technical job markets to deliver the best in class software engineering and exceptional client services.

We have 20+ years of experience in software and hardware development for clients all around the world, especially for US clients. As an official Microsoft Gold Partner, our company is listed in the top 5 software development companies in Illinois, USA.

US clients are leading trading and financial organizations, insurance companies, large healthcare associations, pharmaceutical and energy companies, equipment manufacturers, hi-tech startups, etc.

Areas of expertise are consulting, development, implementation, and support of software solutions. We implement modern backend solutions that support microservices architecture with the following technologies: NET Core, Node.js, Java, SQL Server, Postgre

SQL, Mongo

DB, Redis, Rabbit

MQ. For the web UI front-end development, we opt for React, or Angular, and for mobile development — Swift, Kotlin, Java. Most of the systems are designed for cloud infrastructures like AWS, Azure, GCP, and heavily rely on Docker, Kubernetes while modern CI/CD is made using Git Lab CI or Team City. In September 2021, Velvetech LLC received the status of the official Training Provider of the International Institute of Business Analysis.

This status gives us the right to conduct regular quality trainings for Business Analysts and anyone performing BA activities regardless their job title.

Principles are based on Agile Methodology, Scrum and Kanban. Various projects coded in Git Lab or Git Hub are built with multiple coordinated teams, collaborating via Jira, Confluence, MS Teams, and Slack. Velvetech constantly follows the Tech trends and actively cooperates with startups in such breakthrough areas as Machine Learning, the Internet of Things, Blockchain, FPGA, and AI.

We are looking for a Data QA Engineer with deep expertise in Python and SQL. In this role, you’ll be the vigilant guardian of data integrity, crafting rigorous tests, surfacing hidden anomalies, and telling compelling stories with clean, trusted datasets. Your SQL prowess will probe the depths of our warehouse, while Python scripts orchestrate automated quality checks and deeper analytical insight.

Together, they ensure every data‑driven decision rings true..

• Design and Execute Data Tests: Write SQL queries to validate source-to-target mappings, row counts, referential integrity, and business rules.
• Build reusable Python test suites (PyTest, Great Expectations, or similar) to automate regression and smoke tests across pipelines.
• Monitor and Troubleshoot Pipelines: Track daily ETL/ELT jobs, investigate failures, and triage data incidents to root cause with log analysis and ad-hoc SQL.
• Partner with Data, AI, and BI Engineering to quickly resolve issues and prevent recurrence through robust test coverage.
• Analyze and Communicate Findings: Quantify data quality metrics (completeness, freshness, accuracy) and surface them through dashboards or narrated notebooks.
• Present trends and anomalies to stakeholders, translating complex queries into clear, actionable insights.
• Continuously Improve Process: Champion best-practice coding standards (version control, CI/CD, code reviews).
• Identify opportunities for new data validation checkpoints and performance optimizations.

• SQL – window functions, CTEs, query optimization, profiling large datasets.
• Python (Proficient) – Pandas, PyTest/Great Expectations, data-centric OOP, basic CLI scripting.
• Data Warehousing Concepts – star/snowflake schemas, partitioning, indexing; experience with Snowflake, Redshift, Big Query, etc.
• ETL/ELT Debugging – Airflow, dbt, or similar orchestration tools.
• Analytics Mindset – descriptive statistics, anomaly detection, storytelling.

• Experience with cloud platforms (AWS, GCP, or Azure) and IaC (Terraform, Cloud Formation).
• Familiarity with data observability platforms (Monte Carlo, Metaplane,…