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Sr Data Engineer , 3866
Job Location:
Monthly Salary:
Posted:
19 July 2026 (21 days ago)
Posted:
Application Deadline:
17 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Summary (List Format):
- Design develop and maintain robust ETL pipelines using Data Bricks and Azure Data Factory.
- Transform raw data into actionable insights to support business decision-making.
- Manage and optimize data storage solutions using SQL Server.
- Collaborate with cross-functional teams and stakeholders to gather requirements and ensure seamless data integration.
- Develop and maintain scalable data architectures and data workflows.
- Automate data operations and enhance deployment processes using DevOps practices.
- Write and optimize Python scripts for efficient data processing and analysis.
- Monitor troubleshoot and ensure accuracy and availability of data pipelines.
- Stay updated with industry trends and adopt new data engineering technologies and best practices.
- Ensure high data quality across platforms and facilitate ongoing improvements in data engineering processes.
- Design develop and maintain robust ETL pipelines using Data Bricks and Azure Data Factory.
- Transform raw data into actionable insights to support business decision-making.
- Manage and optimize data storage solutions using SQL Server.
- Collaborate with cross-functional teams and stakeholders to gather requirements and ensure seamless data integration.
- Develop and maintain scalable data architectures and data workflows.
- Automate data operations and enhance deployment processes using DevOps practices.
- Write and optimize Python scripts for efficient data processing and analysis.
- Monitor troubleshoot and ensure accuracy and availability of data pipelines.
- Stay updated with industry trends and adopt new data engineering technologies and best practices.
- Ensure high data quality across platforms and facilitate ongoing improvements in data engineering processes.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
