Apply on Kit Job: kitjob.in/job/4gmd71

Key responsibilities:
Support and monitor weekend batch loads, ensuring timely and accurate execution
Perform outlier detection and root cause analysis for issues such as demand forecast drops or anomalies
Translate findings into explicit insights and communicate them effectively to leads and stakeholders
Monitor scheduled jobs and data pipelines to ensure successful execution
Validate dashboard outputs and analyze data trends, anomalies, and inconsistencies
Support basic model validation and output analysis (e.g., forecast vs actuals, error trends)
Write and optimize SQL queries and PySpark transformations for debugging and analysis
Identify patterns in recurring failures and recommend improvements
Work with data science and engineering teams to debug model or data-related issues
Escalate issues when required, with clear analysis and supporting insights




Monitor workflows in Azure Data Factory (ADF) and Databricks
Contribute to CI/CD validation and release monitoring
Maintain documentation for issues, RCA findings, and fixes

Tech stack required:
3 to 5 years of experience as Machine Learning Engineer
Strong working knowledge of SQL (must-have)
Basic to intermediate PySpark / Python
Understanding of data pipelines and distributed data processing
Familiarity with Azure Data Factory (ADF) and Databricks
Basic understanding of machine learning workflows and model outputs
Ability to perform data analysis and debugging using data
Exposure to CI/CD processes and Azure DevOps

Apply on Kit Job: kitjob.in/job/4gmd71

📌 Machine Learning Engineer (Hyderabad)
🏢 Grid Dynamics
📍 Hyderabad