Data Engineering
1 week ago
SALARY : 10LPA - 16LPA
Job Overview :
Our client is seeking an experienced and detail-oriented Data Engineering and Machine Learning Tester to join our Quality Assurance team. The ideal candidate will have strong expertise in testing data pipelines, machine learning models, and large-scale data processing systems, specifically within the Databricks environment. This role is critical to ensuring the quality, accuracy, and reliability of our data engineering workflows and machine learning solutions.
Key Responsibilities :
Test Planning and Strategy :
- Develop, document, and maintain comprehensive test plans, test cases, and test scripts for data engineering and machine learning workflows.
- Collaborate with data engineers, data scientists, and product managers to understand requirements and define testing strategies tailored to the Databricks environment.
Data Pipeline Testing :
- Validate data ingestion, transformation, and processing workflows within Databricks.
- Perform end-to-end testing of ETL/ELT processes to ensure data accuracy, consistency, and performance.
- Verify data integrity across different stages of the pipeline and ensure that data meets business requirements.
Machine Learning Model Testing :
- Test and validate machine learning models developed on Databricks, ensuring they meet accuracy, performance, and reliability standards.
- Develop and execute tests for model training, validation, and deployment pipelines.
- Evaluate the performance of models on large datasets and ensure that they generalize well to unseen data
Automation and Continuous Integration :
- Implement automated testing solutions for data pipelines and machine learning models using tools compatible with Databricks.
- Integrate automated testing processes into the CI/CD pipeline to ensure continuous quality checks. Azure DevOps experience is a plus.
- Leverage Databricks notebooks and workflows for test automation where applicable.
Performance Testing :
- Conduct performance testing of data pipelines and machine learning models to identify bottlenecks and optimize processing time.
- Test the scalability of data engineering solutions to handle large volumes of data efficiently.
Collaboration and Communication :
- Work closely with cross-functional teams, including data engineers, data scientists, and DevOps, to resolve technical challenges and ensure the quality of data solutions.
- Provide clear and concise feedback on test results and collaborate with teams to address issues.
- Participate in sprint reviews and retrospectives, providing insights on test outcomes and quality metrics.
Qualifications :
Technical Skills :
- Strong experience with Databricks and related tools (Apache Spark, Delta Lake, MLflow).
- Proficiency in Python, SQL, and testing frameworks relevant to data engineering and machine learning.
- Experience with big data technologies on Azure platform.
- Knowledge of testing automation tools and CI/CD pipelines.
- Understanding of data governance, data quality, and data privacy practices.
Experience :
- 3+ years of experience in testing data engineering workflows and machine learning models, with a focus on big data environments.
- Proven experience working within Databricks or similar platforms.
- Prior experience in an Agile development environment is preferred.
Soft Skills :
- Excellent analytical and problem-solving skills.
- Strong communication skills, both verbal and written.
- Ability to work independently and as part of a collaborative team.
Benefits :
- Opportunities for professional growth and development.
- Collaborative and innovative work environment.
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