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Job Info
- Job Identification12764
- Posting Date04/29/2026, 06:35 AM
- Job RoleBusiness Analytics-Analytics
- Experience (In Years)3-6
- Job LocationGurgaon, Bangalore
Job Description
Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest, transform, and process large volumes of structured and semi-structured data.
• Develop and optimize data models, tables, and transformations to support analytics, reporting, and downstream data consumption.
• Work with large datasets using SQL, PySpark, and modern data platforms such as Snowflake and Databricks to ensure efficient data processing.
• Build and manage data workflows using orchestration tools such as Apache Airflow, ensuring reliable and timely data delivery.
• Develop automation scripts using Shell Scripting and Python to support data pipeline execution, monitoring, and operational efficiency.
• Monitor, troubleshoot, and optimize data pipelines to improve performance, scalability, and reliability across the data ecosystem.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and enable data-driven insights
• Ensure adherence to data engineering best practices, including data quality checks, documentation, and pipeline governance.
Responsibilities
-
Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest, transform, and process large volumes of structured and semi-structured data.
-
• Develop and optimize data models, tables, and transformations to support analytics, reporting, and downstream data consumption.
-
• Work with large datasets using SQL, PySpark, and modern data platforms such as Snowflake and Databricks to ensure efficient data processing.
-
• Build and manage data workflows using orchestration tools such as Apache Airflow, ensuring reliable and timely data delivery.
-
• Develop automation scripts using Shell Scripting and Python to support data pipeline execution, monitoring, and operational efficiency.
-
• Monitor, troubleshoot, and optimize data pipelines to improve performance, scalability, and reliability across the data ecosystem.
-
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and enable data-driven insights
-
• Ensure adherence to data engineering best practices, including data quality checks, documentation, and pipeline governance.
Qualifications
-
Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest, transform, and process large volumes of structured and semi-structured data.
-
• Develop and optimize data models, tables, and transformations to support analytics, reporting, and downstream data consumption.
-
• Work with large datasets using SQL, PySpark, and modern data platforms such as Snowflake and Databricks to ensure efficient data processing.
-
• Build and manage data workflows using orchestration tools such as Apache Airflow, ensuring reliable and timely data delivery.
-
• Develop automation scripts using Shell Scripting and Python to support data pipeline execution, monitoring, and operational efficiency.
-
• Monitor, troubleshoot, and optimize data pipelines to improve performance, scalability, and reliability across the data ecosystem.
-
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and enable data-driven insights
-
• Ensure adherence to data engineering best practices, including data quality checks, documentation, and pipeline governance.
Required Skills
- Adapting To Change
- Attention To Consistency
- D3 Data Visualization
- Interpersonal Dynamics with Coworkers
- Results Orientation
- SQL Analysis
- Statistical Analysis
- Time Management Skills
- Working under Pressure
- Writing Communication Skills
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