Data Engineer - DBT

Monocept • Python • SQL • ETL/ELT • 1 month ago
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Salary
≈ $16k – $40k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Middle · 4+ years exp
Employment
Full-Time

First seen by Alion on Sep 24, 2026.

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Monocept

Monocept is an Indian technology services company that builds scalable data pipelines and cloud-based data platforms. Its engineers work with AWS services, data modeling, ETL and ELT frameworks and the dbt modern data stack, and the company hires data engineers with four to six years of experience. The company is based in Gurgaon, India.
monocept.ai • HQ: Gurgaon, India • Custom Software Development • Data Engineering & Migration Services
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 modelling 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
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