AWS Data Engineer

Emids; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A growing tech company is seeking a skilled Data Engineer to join their team in Bengaluru. The role involves designing and optimizing scalable data pipelines using technologies like AWS, Databricks, and PySpark. Ideal candidates should have 4+ years of experience in data engineering and strong problem-solving skills, along with relevant degrees. This position offers the opportunity to collaborate across teams to deliver data-driven solutions in a dynamic environment.

Qualifications

• 4+ years of hands-on experience in Data Engineering.
• Strong expertise in PySpark, Databricks, and Airflow for large-scale data processing and orchestration.
• Solid experience with AWS services such as S3, Glue, Redshift, EMR, Lambda, and IAM.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Airflow.
• Build and optimize data models and data lakes/warehouses on AWS.
• Implement best practices for data quality, data governance, and performance optimization.

Skills

AWS

Databricks

PySpark

Airflow

SQL

Problem-solving

Communication

Education

Bachelor’s/Master’s degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Job description

We are looking for a highly skilled Data Engineer with strong expertise in AWS, Databricks, PySpark, and Airflow to join our growing Data Engineering team. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and solutions that enable advanced analytics, machine learning, and business intelligence across the organization.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Airflow.
• Build and optimize data models and data lakes/warehouses on AWS.
• Implement best practices for data quality, data governance, and performance optimization.
• Collaborate with cross‑functional teams (data scientists, analysts, product, and business teams) to deliver data‑driven solutions.
• Ensure reliability, scalability, and efficiency of data workflows through automation and monitoring.
• Troubleshoot complex data engineering issues and optimize processing performance.

Required Skills & Qualifications

• Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.
• 4+ years of hands‑on experience in Data Engineering.
• Strong expertise in PySpark, Databricks, and Airflow for large‑scale data processing and orchestration.
• Solid experience with AWS services such as S3, Glue, Redshift, EMR, Lambda, and IAM.
• Strong knowledge of SQL and performance tuning.
• Experience with CI/CD pipelines, Git, and containerization (Docker/Kubernetes) is a plus.
• Strong problem‑solving skills, communication, and ability to work in a fast‑paced environment.

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