Experience
6 - 11 yrs
Job Location
Prayagraj, India
Vacancy
1
Designation
Ai Ml Engineer
Job Type
Not specified
Job Description
Total Exp :-6+ Years
Work Mode :- Remote
Job Type :- Remote
Work Mode :- Remote
Job Type :- Remote
The candidate will be required to be on Deqodes payroll. Please connect for any further clarification.
Must Have Skills- PySpark, Azure Databricks, SQL, Python
Requires strong SQL, working knowledge of PySpark/Python, and experience with data pipelines, Azure Data Factory, Databricks, and basic ML workflows.
Involves stakeholder communication, CI/CD monitoring, and continuous improvement through debugging, pattern identification, and data-driven insights.
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 clear 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.
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.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 clear 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.
No Referrers Available
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