Jobs at OneMagnify

Partner with engineering and data teams to design and execute automated and manual tests for high-volume data pipelines and APIs. Build and maintain test frameworks, author complex SQL for validation, perform UAT and production smoke tests, analyze defects, and drive release governance. Advocate shift-left testing, integrate tests into CI, document test evidence for audits, and continually improve QA tools and processes. Role requires working 5:00 PM–1:30 AM IST and active participation in Agile ceremonies.

Build, deploy, and operate production ML and generative AI systems. Implement MLOps practices (experiment tracking, model versioning, CI/CD), design scalable serving architectures, monitor model performance and data drift, and collaborate with data scientists, engineers, and clients to operationalize AI across digital and marketing platforms.

The role involves managing ML models, deploying them in production, evaluating technologies, and implementing CI/CD processes while supporting model development and ensuring data security.

OneMagnify is seeking HR interns placed in various teams to support client services, analytics, creative, IT, and talent management initiatives, requiring interpersonal skills and analytical interest.

Perform BI and data analysis by building Power BI dashboards, managing GCP data pipelines (BigQuery, Data Fusion), writing SQL, modeling data (star/dimensional), and presenting insights to leadership.

The Enterprise Quality Architect will design scalable quality frameworks, define automation strategies, oversee quality governance, and integrate testing into CI/CD pipelines, requiring strong proficiency in Python and SQL.

Lead design and delivery of scalable data platforms and production-grade pipelines using Databricks and cloud providers. Build batch and real-time ETL, implement data models for analytics, ensure data quality and governance, integrate AI/GenAI capabilities, mentor junior engineers, and drive client-facing technical discussions and architecture reviews.

The role involves developing credit risk models, enhancing AI solutions, conducting statistical analyses, and collaborating with quantitative analytics teams while ensuring adherence to data privacy standards.

Optimize LLM performance and implement evaluation frameworks; build clustering models for customer and product segmentation; design and maintain data pipelines using SQL and Python DAGs.

Drive product quality by independently creating and executing test plans, automated test suites (preferably Playwright) integrated with CI/CD, and validating complex payment and data scenarios using advanced SQL and analytics. Collaborate with Product and Engineering, support UAT, document requirements as needed, and lead continuous improvement of testing practices and data validation.