Data Engineer

Scrini Ai; Bengaluru; Hybrid; INR 1,500,000 - 2,500,000; Full time

Job summary

Scrini Ai in Bengaluru is seeking a Data Engineer for a full-time hybrid role focused on building reliable data pipelines and improving data quality. The position requires 4-6 years of experience with Python, SQL, Spark, and AWS to support data engineering for a SaaS platform.

You will develop data solutions, ensure dependable data operations, and contribute to scalable data infrastructure within a dynamic team.

Qualifications

• 4-6 years of experience in data engineering.
• Experience with Python.
• Experience with SQL.
• Experience with Apache Spark.
• Experience with AWS.
• Experience building reliable data pipelines.
• Experience improving data quality.

Responsibilities

• Build reliable data pipelines to support the companys data engineering needs.
• Improve data quality across data pipeline workflows.
• Use Python and SQL to develop and support data engineering solutions.
• Apply Apache Spark to data processing and pipeline development activities.
• Use AWS within data engineering and data pipeline workflows.
• Contribute to dependable data operations in a SaaS environment.

Skills

Data pipelines

Data quality

Tools

Python

SQL

Apache Spark

AWS

Job description

We are hiring a Data Engineer to join a SaaS company in Bengaluru. This full-time, hybrid role requires 4-6 years of experience with Python, SQL, Apache Spark, and AWS, with a focus on building reliable data pipelines and improving data quality.

Key Responsibilities

• Build reliable data pipelines to support the companys data engineering needs.
• Improve data quality across data pipeline workflows.
• Use Python and SQL to develop and support data engineering solutions.
• Apply Apache Spark to data processing and pipeline development activities.
• Use AWS within data engineering and data pipeline workflows.
• Contribute to dependable data operations in a SaaS environment.

Required Qualifications

• 4-6 years of experience in data engineering.
• Experience with Python.
• Experience with SQL.
• Experience with Apache Spark.
• Experience with AWS.
• Experience building reliable data pipelines.
• Experience improving data quality.