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Role: Senior Quality Engineer - ETL Testing, Data Quality Testing, and Test Automation 7+ years Summary: We are seeking a highly technical QE Tester to lead quality assurance for our data-driven ecosystem Core Responsibilities End-to-End Data Validation: Lead testing for complex data pipelines, ensuring integrity from source systems through the Medallion Architecture (Bronze, Silver, Gold layers). Advanced SQL Testing: Write sophisticated queries to validate complex transformations, including advanced joins, window functions, and SCD (SCD1 vs SCD2) logic. LLM & Agentic Evaluation: Develop and execute frameworks to detect LLM hallucinations, bias, and non-deterministic output inconsistencies. Performance & Governance: Conduct stress testing on AI agents, monitor token costs, and validate guardrails to ensure protected and cost-effective AI operations. Cooperative Quality: Partner with Data Engineers and AI Researchers to define "Golden Datasets" and establish business-rule validation criteria. Technical Requirements Data Engineering Validation: Advanced SQL: Expertise in complex analytical queries, window functions, and validating Slowly Changing Dimensions (SCD). Warehousing Fundamentals: Deep understanding of Fact vs Dimension validation and Source-to-Target (STT) reconciliation. Pipeline Integrity: Proven experience with Incremental vs Full Load testing, row count reconciliation, and data completeness checks. Data Quality (DQ): Ability to design automated DQ checks, data profiling, and validation of business-specific transformation rules. API Testing: Proficient in validating RESTful APIs and alternative integration patterns. LLM & Generative AI Validation: Prompt Engineering: Validating system prompts, user prompts, and few-shot learning impacts on model behavior. Hallucination & Bias Detection: Implementing techniques to identify factual inaccuracies and social biases in model responses. Model Parameters: Testing the impact of Temperature, Top-P, and Conte .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.