Architect - Quality Engineering

Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our solutions, our 4800+ tribe is solving problems that eventually impact the lives of millions globally. Our culture is modeled around expertise and respect with a team first mindset. Headquartered in Silicon Valley, you'll find our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and Singapore, including a substantial remote global workforce.

We're Great Place to Work-Certified. Working at Tiger Analytics, you'll be at the heart of an AI revolution. You'll work with teams that push the boundaries of what is possible and build solutions that energize and inspire.

As an QE Solution Architect, you will be involved in designing and building automation initiatives including Framework development using various AI services. More specifically, you will work on:

. 10-12+ years of experience in Data Testing / Data Quality Engineering, Application Testing, API / Microservices Testing, Mobile (iOS or Android) Testing, Performance Engineering.

. Build AI-driven solutions for quality and audit purposes

. Designing Frameworks, developing Proof of concepts, Accelerators, and executingeffectively/independently.

. Designing and implementing python utilities to enhance productivity for Enterprise Products like Data, Apps, BI, API, Mobile etc. with GenAI / LLM intervention.

. Building simplified interfaces as part of framework design in order to facilitate features such as easy to maintain, easy to enhance, high reusability and scalability factors in mind.

. Taking part in Demos, Planning, Proposals, etc., with the rest of the team.

. Collaborating with business consultants, data scientists, engineers, and application stakeholders.

. Strong background in building robust Python-based systems and SQL knowledge

. Architect QE solutions on cloud platforms such as Azure (ADLS, Databricks, ADF, Synapse), AWS (Glue, Lambda, Aurora, Redshift), GCP (Big Query, GKE), Snowflake or equivalent.

. Familiarity with containerization, orchestration, and scalable architecture

. Knowledge of natural language processing (NLP) is a must.

. Hands-on experience with multiple LLMs like OpenAI, Claude, Gemini, Llama, etc. along with implementation of AI Agents and Model Context Protocols (MCP).

. Knowledge of using hyperscaler products like Hadoop, Pyspark, Databricks, Snowflake and AWS EMR

. Strong Experience in building multiple frameworks using Streamlit, Pytest, Playwright, Selenium, Seaborn, Plotly, Langchain, LangGraph, Appium, Robot and related Libraries.

. Strong knowledge of CI/CD pipeline (Airflow/Azure DevOps/Jenkins/GitHub Actions)

. Ability to independently design, develop and architect highly available, highly scalable accelerators and frameworks from scratch

. Proficiency in data manipulation libraries like pandas or NumPy for Python and experience with data visualization tools to build analytical models and statistics as required.

. Good knowledge of RESTful interfaces / Microservices concepts

. Good to have experience with GenAI, LLMs, RAG pipelines, and vector databases (Pinecone, FAISS)

. Define and implement data quality engineering frameworks for data lakes, data warehouses, and analytics platforms.

. Architect and implement data test automation using Python, SQL, and data testing frameworks.

. Define data quality KPIs, dashboards, and metrics.

. Identify risks related to data accuracy, latency, and compliance and communicate them proactively.

. Partner with data engineers, product owners, and architects to drive quality from design to delivery.

. Mentor QE engineers and SMEs.

. Review test strategies, frameworks, and implementations.

. Support proposal discussions, estimations, and solutioning from QE perspective

. Understanding of the concepts involved in Functional & Non-Functional validations

. Knowledge of Dockers and Kubernetes or containers is good to have

. Ability to quickly learn and apply complex technical information to automation solutions.

. Attention to detail and ability to effectively escalate issues and manage escalations.

. Experience with Agile methodology

. Ability to handle multiple assignments at one time and meet delivery dates.

. Project Management Tools like ADOTestPlans/ALM/Rally/JIRA knowledge is a plus.

. Additional programming languages like Java, JavaScript, Rust or R knowledge is a plus.

. Excellent written and communication skills.