ETL Senior Data Engineer

2 weeks ago


Delhi, Delhi, India Seraro Full time


Job Locations:
- PUNE SEZ QUBIX

Required Experience:
- Years

Skills:
- Azure, Automation

Senior Data Engineer:

Qualifications:
- 10+ years of experience (including 5+ years on Azure) in Data Engineering, ETL & Data Warehousing.

Should have experience in designing and developing metadata-driven automated pipelines for ingesting and processing data from various sources into Azure cloud.


Experience in implementing automated data quality checks, error handling, and data validation checks based on metadata configuration.

Experience in creating repeatable and reusable data pipeline modules.

Experience in controlling pipeline dependency management, parallel execution, priority, etc., through metadata configurations.
Knowledge of Azure Data Factory, Databricks, SSIS, Azure Functions, Logic Apps, Azure Event Hubs, PySpark, Spark Streaming, ADLS Gen2, Azure Blob, Azure Synapse, Azure SQL, SQL Server, and working knowledge of Tableau.

Nice to have:
- Experience in designing & building metadata data models.
- Experience in Batch, API, Event, Streaming data processing.

Experience in building CI/CD pipelines using Azure DevOps, GitHub, Jenkins, etc.
Knowledge of handling various file formats like JSON, XML, CSV, Parquet, Delta, etc.

Experience in creating complex Databricks notebooks and integrating with Azure Ecosystem.
Experience in Azure Cloud Data Warehousing projects.
Excellent communication & client-facing skills.
Knowledge of Agile/SAFe methodology.
Experience in a global delivery model.
Experience in working with product managers, project managers, business users, applications development team members, DBA teams, and Data Governance team daily to analyze requirements and develop technical solutions.

Responsibilities:
- Work with business and technology stakeholders to gather and understand their requirements.
- Design, build, and deploy repeatable modules using state-of-the-art techniques.
- Build a metadata-driven automation framework.
- Integrate data from various sources to provide a unified view for analytics and reporting.
- Design and build metadata data models for the automation framework.
- Provide technical support to a team of data engineers, guiding them in implementing best practices and innovation.

Collaborate with cross-functional teams to deliver end-to-end data solutions meeting business requirements.



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