
Specialist Data/AI Engineering
- Hyderabad, Telangana
- Permanent
- Full-time
- Develop and implement QA frameworks, test plans, and automated testing scripts for data pipelines and AI/ML models.
- Validate data quality, consistency, and accuracy across ingestion, transformation, and storage processes.
- Test AI/ML model performance including accuracy, bias, robustness, and drift detection.
- Utilize cloud platforms (AWS, Azure, GCP) and modern data technologies (e.g., Snowflake, Databricks, Kafka) to manage large-scale data workflows.
- Collaborate with data engineers, data scientists, and product teams to identify test requirements and ensure comprehensive coverage.
- Perform regression, integration, system, and performance testing on data and AI workflows.
- Automate testing processes using appropriate tools and frameworks to enable continuous testing in CI/CD pipelines.
- Monitor production systems to detect issues proactively and support root cause analysis for defects or anomalies.
- Document test results, defects, and quality metrics, communicating findings to technical and non-technical stakeholders.
- Advocate for quality best practices and contribute to improving testing methodologies across the CDO.
- Stay current with industry trends and emerging tools in data engineering, AI, and QA automation.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- Experience in quality assurance or testing roles focused on data engineering, AI, or machine learning systems.
- Proficiency in programming and scripting languages such as Python, SQL, and experience with test automation frameworks.
- Strong understanding of data pipelines, ETL/ELT processes, and data validation techniques.
- Familiarity with machine learning concepts and model evaluation metrics.
- Experience with cloud platforms (AWS, Azure, GCP) and data platforms (Snowflake, Databricks) is preferred.
- Knowledge of CI/CD tools and integration of automated testing within deployment pipelines.
- Excellent analytical, problem-solving, and communication skills.
- Experience with AI/ML model testing frameworks and bias/fairness testing.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) environments.
- Understanding of data governance, compliance, and responsible AI principles.
- Experience with real-time data streaming and testing associated workflows.