Data Engineer - DBT

Monocept; Gurugram District; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

Monocept is looking for a skilled Data Engineer to design, develop, and maintain scalable ETL/ELT data pipelines. You will work with AWS services including S3, Lambda, and Glue to implement data lake and warehouse solutions while ensuring data quality and reliability.

The ideal candidate should have 4-6 years of experience in data engineering with solid expertise in Python, PySpark, and SQL. A strong understanding of DevOps practices and modern data stack tools, including dbt, is also required.

Qualifications

• 4-6 years of strong hands-on experience in data engineering.
• Solid expertise in AWS cloud services and data modeling concepts.
• Proficiency in Python, PySpark, and SQL/PLSQL.

Responsibilities

• Design and maintain ETL/ELT data pipelines using Python and PySpark.
• Implement data lake and warehouse solutions for BI needs.
• Collaborate with teams to support analytics and reporting.

Skills

AWS cloud services

Python

PySpark

SQL/PLSQL

Data modeling

Data warehousing

DevOps practices

CI/CD pipelines

ETL/ELT frameworks

Monitoring and observability

Tools

AWS S3

AWS Lambda

AWS EMR

AWS Glue

AWS Redshift

AWS RDS (Postgres)

AWS Athena

dbt

Jenkins

Terraform

GitLab

Job description

Job Title: Data Engineer - DBT

Experience: 4-6 Years

Location: GGN

Job Description

We are looking for a skilled Data Engineer with strong hands-on experience in building and maintaining scalable data pipelines and cloud-based data platforms. The ideal candidate should have solid expertise in AWS services, data modeling, ETL frameworks, and modern data stack practices.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python, PySpark, SQL/PLSQL.
• Work extensively with AWS services such as S3, Lambda, EMR, Glue, Redshift, RDS (Postgres), Athena, and dbt.
• Implement and manage data lake and data warehouse solutions to support BI and analytics use cases.
• Develop and optimize data models and ensure best practices for modern file and table formats.
• Optimize Spark jobs for performance, cost, and scalability.
• Implement CI/CD pipelines for data workflows using DevOps tools like Jenkins, Terraform, and GitLab.
• Set up and maintain logging, monitoring, alerting, and dashboards for cloud and data solutions.
• Ensure data quality, reliability, and observability across pipelines.
• Collaborate with cross-functional teams to support analytics and business reporting needs.

Required Skills & Qualifications

• Strong hands-on experience with AWS cloud services for data engineering.
• Proficiency in Python, PySpark, SQL/PLSQL.
• Solid understanding of data modeling and data warehousing concepts.
• Experience with modern data stack tools (including dbt).
• Working knowledge of DevOps and CI/CD practices for data pipelines.
• Experience in setting up monitoring and observability for data platforms.