Full-Time
Senior Quality Engineer
AI
Posted on 9/23/2025
Matillion
201-500 employees
AI-powered data pipeline management platform
No salary listed
Hyderabad, Telangana, India
Hybrid
Hybrid role requiring some in-office presence.
 QA & Testing (3) |
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- Strong experience with end-to-end testing of distributed systems and SaaS applications.
- Deep understanding of testing methodologies including exploratory, regression, risk-based, performance, and security testing.
- Skilled in writing automated tests using tools like Cypress, Pact, or similar frameworks, with coding experience in Java/JavaScript.
- Solid understanding of the Test Pyramid, CI/CD pipelines, and agile methodologies (Scrum, Kanban).
- Experience working with cloud platforms like AWS, GCP, or Azure, plus comfort with SQL and database testing.
- A team player with a QA-first mindset and a drive to elevate engineering standards across the board.
- Hands-on experience working with LLM APIs like OpenAI, Anthropic, or HuggingFace.
- Familiarity with prompt engineering, fine-tuning prompts for desired outcomes.
- Practical experience using Retrieval-Augmented Generation (RAG) to enrich LLM responses.
- Understanding of key GenAI concepts like system/user prompts, tokens, embeddings, temperature, top-p, context windows, and stop sequences.
- Champion a shift-left testing culture by embedding quality across every phase of our software development lifecycle.
- Design, build, and maintain robust test automation frameworks for functional, integration, performance, security, and accessibility testing.
- Collaborate closely with product managers, developers, and AI engineers to test and evaluate LLM-integrated features using both traditional and GenAI-specific testing methods.
- Implement tools and techniques to test LLM-based functionality, including prompt evaluation, RAG-enhanced responses, and API behavior.
- Drive the use of modern CI/CD pipelines, ensuring testing is efficient, scalable, and automated wherever possible.
- Analyze, interpret, and share meaningful insights from test results – especially when comparing LLM model responses, prompt outcomes, and system behavior.
- Mentor team members in test strategies, automation practices, and GenAI testing methodologies.
- Continuously assess and improve the quality landscape, identifying opportunities to increase speed, accuracy, and innovation in how we test.
- Experience with fine-tuning LLMs or training smaller models for specific tasks.
- Familiarity with prompt compression techniques and advanced GenAI patterns like prompt chaining, agentic workflows, or LLM routing.
- Exposure to abstraction libraries such as Spring AI or similar.
- Experience with LLM eval frameworks to benchmark model performance and prompt effectiveness.
Matillion builds a data management platform that helps data teams build, manage, and orchestrate data pipelines. The platform supports moving, transforming, and orchestrating data from many sources using a library of hundreds of connectors, with both no-code and code-based options (SQL, Python, dbt). AI features integrate large language models into pipelines and automatically generate documentation to boost data literacy. Pricing is usage-based, so clients pay for what they use, enabling easy scaling as needs grow. Matillion differentiates itself by its AI-enabled pipeline automation, a unified view that covers no-code to code workflows, and a broad connector ecosystem. The company aims to boost data team productivity by making data pipelines faster to build and easier to manage, while improving data literacy across the organization.
Company Size
201-500
Company Stage
Series E
Total Funding
$309.4M
Headquarters
Altrincham, United Kingdom
Founded
2010
Simplify's Take
What believers are saying
- Tim O'Neil as CRO scales Maia sales to enterprises like Merck.
- Precisely OEM embeds Matillion ELT for multi-cloud AI readiness.
- $100M funding expands no-code platform amid developer shortage.
What critics are saying
- Snowflake Unistore erodes Maia value in 6-12 months.
- Databricks Lakeflow captures customers in 12-18 months.
- Precisely partnership diverts revenue in 3-6 months.
What makes Matillion unique
- Maia AI agents build end-to-end pipelines from natural language prompts.
- Migration Agent converts ETL from 14 platforms to ELT in weeks.
- Hundreds of connectors enable data movement across any cloud platform.
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Benefits
Company Equity
Health Insurance
Life Insurance
401(k) Retirement Plan
Paid Vacation
Mental Health Support
Hybrid Work Options
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 1%2 year growth
↓ -1%Matillion has launched Migration Agent, a new capability within its Maia AI Data Automation platform that autonomously converts legacy ETL pipelines to modern cloud data warehouses. The tool supports migration from 14 platforms, including Informatica PowerCenter, Alteryx, IBM DataStage and SSIS, to Snowflake, Databricks and Amazon Redshift. Migration Agent parses transformation logic, dependency graphs and pipeline metadata, then reconstructs each pipeline as a warehouse-optimised ELT pipeline. Unlike conventional migration tools, it flags unsupported or ambiguous constructs for human review, compressing what typically requires multi-quarter consulting engagements into weeks. The capability is available now, with Matillion hosting a live webinar on 31st March demonstrating the conversion of 100 Informatica pipelines in 30 minutes.
Matillion has appointed Tim O'Neil as Chief Revenue Officer to scale its enterprise go-to-market strategy amid growing demand for its AI Data Automation platform, Maia. O'Neil joins from leadership roles at Alation and ThoughtSpot, bringing extensive experience in enterprise data software. The appointment follows strong adoption of Maia, which organisations including Merck, EDF and GE Healthcare are using to automate data workflows. The platform integrates with Snowflake, AWS and Databricks, and leverages AI models from labs like Anthropic to deliver automation within existing enterprise systems. Matillion achieved unicorn status in 2021 and serves thousands of enterprises globally, including Cisco, London Stock Exchange Group and ServiceNow. Maia uses autonomous AI agents to design, build and maintain data pipelines, enabling data teams to focus on delivering data products.
Precisely and Matillion speed data modernisation and AI readiness. March 12, 2026 Precisely and Matillion have agreed on a new OEM partnership. It will see Matillion's cloud-native Extract-Transform-Load (ELT) capabilities embedded into the Precisely Data Integrity Suite. It gives customers a single suite of tools that allows them to accelerate the modernisation of their data environments. More importantly, it will speed up the transformation of data for use in AI. Ulf Viney, Executive Vice President of Engineering, Support & Operations at Precisely, said, "AI ambition only delivers ROI when the data behind it is modern, scalable, and trustworthy. "By embedding cloud-native ETL directly into the Data Integrity Suite, we're eliminating fragmentation and giving organizations a unified foundation to move, prepare, and trust their data, accelerating their path to Agentic-Ready Data." How does this deal accelerate data transformation? One of the core processes in data transformation is ETL. Systems extract data from source locations, often with different attributes and object names. Then they transform the data so it becomes part of a unified set. As part of that process, the transformation corrects and enriches the data based on business rules. The result is a higher quality and consistent data set. Once systems transform the data, they load it into a new target system. That makes it the source of truth for new applications. Users can query it, use it for complex analysis, and feed decision-making systems. Increasingly, teams also use that data to support new AI-driven applications. However, research from Precisely and the Drexel University LeBow College of Business shows a problem. The recent Precisely 2026 State of Data Integrity and AI Readiness report (registration required) shows that organisations are concerned about their data integrity status. This is impacting AI projects and making it hard for organisations to show ROI from their investments. Embedding Matillion ETL creates a smoother workflow. Embedding the Matillion ETL into the Data Integrity Suite lets customers build automated pipelines to manage their data. This ability lets them create proven, trusted, repeatable, and scalable processes. These automated pipelines also let data teams build self-service options for users. Users can drag and drop data from different sources. Enrichment is then assigned to that data using other drop-down boxes, giving users control over the level and type of enrichment. Another benefit: many customers use multiple clouds. That means data must be pulled from different sources, which often require different tools. Matillion ETL is a cloud-native solution. It runs in the cloud and accesses data across any cloud storage service. Among the benefits that Precisely says this partnership will deliver are: * Low-code, cloud-native ETL/ELT for rapid pipeline development * Scalable data transformation across hybrid and multi-cloud environments * Faster time-to-insight for analytics and reporting * Trusted data foundations for AI and advanced decision-making * Reduced complexity through unified integration workflows Enterprise times: what does this mean? Many of the challenges that organisations struggle with today are nothing new. They have been around for decades. They are often still using multiple tool sets and doing processes such as ETL manually. Additionally, the volume of data they are working with continues to grow and become more complex. The target usage for the data from advanced analytics to decision-making systems and AI continues to evolve. That means pulling data from a wider variety of sources and being able to carry out deeper enrichment of the data. Without this, the data will deliver mediocre solutions that will fall short of the demands from the business teams. To ease things for customers, Precisely has been investing heavily in data sets for enrichment and adding AI capabilities. Now it is adding more traditional tools into the Data Integrity Suite with Matillion ETL. For customers, this will enable them to speed up data transformation and create greater automation. The question now is what will Precisely add next? February 26, 2026 March 11, 2026
Precisely, a data integrity company, has partnered with Matillion to add Extract Transform Load (ETL) capabilities to its Data Integrity Suite's Data Integration service. The OEM partnership enables organisations to move, transform and prepare data within a single suite, eliminating fragmented tools and manual processes. The cloud-native ETL integration combines Matillion's transformation platform with Precisely's broader suite, which includes data quality, governance and enrichment services. The offering supports low-code pipeline development, scalable transformation across hybrid and multi-cloud environments, and faster time-to-insight for analytics. ETL powered by Matillion is now available as part of the Precisely Data Integrity Suite's Data Integration Service. The partnership aims to help organisations modernise data environments and prepare for AI-driven initiatives.
Matillion, a UK-based cloud data analytics firm, has raised $100 million in a funding round led by Lightspeed Venture Partners. The investment aims to expand Matillion's no-code data platform, which simplifies data integration for non-technical users amid a global developer shortage. The funding will enhance product capabilities, scale operations, and strengthen cloud provider partnerships, positioning Matillion at the forefront of cloud data integration and analytics automation.