Senior Data QA - Onshore

🔥 6 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🔧 QA Engineer (Quality Assurance)

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

v4c.ai

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

v4c. ai is a Databricks-focused data and AI services firm that helps enterprises modernize data platforms and accelerate AI initiatives. They provide advisory, migration, MLOps, generative AI, and data governance services, plus prebuilt migration accelerators and production-ready ML pipelines to reduce time-to-value. v4c. ai serves regulated and data-intensive industries (financial services, retail, manufacturing, healthcare) and emphasizes Databricks implementation, scalable model deployment, and long-term operational support.

📋 Description

• Architect, build, and scale automated test frameworks from scratch natively within Databricks using PySpark, Python, and SQL • Design automated assertions for Delta Lake tables, including data drift, schema evolution, and historical data validation via time-travel functions • Validate large-scale batch and real-time streaming data pipelines using Structured Streaming, ensuring source-to-target integrity • Programmatically verify data lineage, audit logs, and access controls implemented via Databricks Unity Catalog • Lead integration of automated data quality tests into enterprise CI/CD pipelines using Azure DevOps, GitHub Actions, Databricks Workflows, APIs, or Airflow • Act as the subject matter expert for data quality, mentor junior team members, establish QA standards, and advocate for data quality principles • Design and execute automated performance and scalability tests on Spark jobs, large clusters, and complex query optimizations

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related quantitative field • 8+ years of experience in data engineering, data QA, or software development engineering in test (SDET) • At least 2+ years of dedicated experience architecting test automation in Databricks • Mastery of Python and PySpark (DataFrames and SQL APIs) for processing and profiling large datasets • Deep expertise in writing advanced SQL queries, optimization techniques, and understanding Spark query execution plans • Hands-on mastery of big-data validation libraries, such as Great Expectations, pytest, and Delta Live Tables expectations • Strong operational knowledge of Databricks deployment on AWS, Azure, or GCP • Preferred: Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional • Preferred: Experience validating real-time event-streaming architectures such as Kafka, Event Hubs, or Kinesis • Preferred: Solid understanding of DataOps culture, testing infrastructure as code, and data observability principles