Senior Data Engineer

N Consulting Limited; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

N Consulting Limited is seeking a Senior Data Engineer in Bangalore to build and maintain scalable data pipelines and cloud-based solutions. The ideal candidate should have 6-10 years of experience with strong skills in Python, PySpark, SQL, and AWS amongst other technologies.

As a Senior Data Engineer, you will be responsible for developing ETL/ELT workflows, managing Snowflake data warehouse environments, and collaborating with cross-functional teams to ensure data quality and reliability.

Qualifications

• 6-10 years of experience in data engineering roles.
• Strong hands-on experience in designing ETL/ELT pipelines.
• Expertise in optimizing performance in Snowflake environments.

Responsibilities

• Build and maintain scalable data pipelines and cloud-based solutions.
• Develop ETL/ELT workflows using PySpark and Python.
• Ensure data quality, performance, and security.

Skills

Python

PySpark

SQL

Hadoop

Snowflake

AWS

Tools

Git

CI/CD tools

Job description

Senior Data Engineer

Location: Bangalore

Experience: 6-10 Years

Required Skills

• Strong hands‑on experience in Python, PySpark, SQL, Hadoop, Snowflake, and AWS.
• Expertise in designing and developing scalable ETL/ELT pipelines and data processing solutions.
• Experience working with AWS services such as S3, Glue, EMR, Lambda, Redshift, and Athena.
• Strong knowledge of Snowflake Data Warehouse, data modeling, performance tuning, and optimization.
• Experience with Big Data technologies including Hadoop, Hive, and Spark.
• Advanced SQL skills with experience in query optimization and data warehousing concepts.
• Knowledge of CI/CD tools, Git, and Agile methodologies.

Responsibilities

• Build and maintain scalable data pipelines and cloud‑based data solutions.
• Develop and optimize ETL/ELT workflows using PySpark and Python.
• Manage and enhance Snowflake data warehouse environments.
• Collaborate with cross‑functional teams to support analytics and reporting requirements.
• Ensure data quality, performance, security, and reliability.