Position:
Data Engineer

Job Description:
Key Responsibilities
Data Pipeline Support & Monitoring
Monitor and support DataOps pipelines across Azure Data Factory, Azure Databricks, and related services.
Identify pipeline failures, performance degradation, and data quality issues.
Ensure SLA adherence and operational stability in a 24×7 production setting.

Incident Management & Troubleshooting
Perform troubleshooting of failed pipelines, Databricks jobs, and Python/PySpark scripts.
Execute resolution (job restarts, pipeline re-runs, alert analysis) and escalate when needed.
Perform deep-dive analysis, identify root causes, and implement permanent fixes.
Conduct and document Root Cause Analysis (RCA) for recurring and high-severity incidents.

Development & Fix Implementation
Analyze and fix issues in Python, PySpark, SQL, and pipeline configurations.
Improve error handling, stability, and performance of data workflows.
Follow change management and deployment processes for production fixes.

Power BI & Data Validation




Support Power BI datasets and dashboards, including refresh failures and data inconsistencies.
Validate data accuracy, completeness, and freshness across pipelines and reporting layers.
Resolve advanced data/model issues and performance concerns.

Collaboration & Continuous Improvement
Act as escalation support (L2) and guide L1 engineers during incidents.
Maintain runbooks, incident records, and shift handover documentation.
Identify automation and monitoring improvements to reduce operational overhead.

Required Skills & Qualifications
4-year bachelor’s degree or equivalent
1–2 years of work experience
Hands-on experience with Azure Data Factory, Azure Databricks, or similar data pipelines technologies.
Solid understanding of Python programming and OOP concepts.
Working knowledge of PySpark and data processing frameworks.
Familiarity with Power BI dataset refreshes and data troubleshooting.
Basic unde

📌 Data Engineer Pune
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📍 Pune