Data Engineer (DBT)

Tata Consultancy Services; Gurugram District; On-site; INR 1,200,000 - 2,300,000; Full time

Job summary

Tata Consultancy Services in Gurgaon seeks a Data Engineer (dbt) to design, build, and maintain scalable data transformation pipelines and analytics-ready models. You will work with dbt, SQL, and cloud data platforms to deliver reliable data solutions in a collaborative environment.

The ideal candidate has 4–8 years of experience with modern data stacks, data warehousing, and CI/CD for data workflows, and will contribute to end-to-end data engineering initiatives.

Qualifications

• dbt and SQL are essential for building data pipelines and models.
• Experience designing scalable data models and star schemas.
• Deep knowledge of modern cloud data platforms and ELT concepts.
• Hands-on with data warehousing concepts and best practices.
• Proficient with version control and CI/CD for data workflows.

Responsibilities

• Design, build, and maintain data transformation pipelines using dbt.
• Develop scalable, reusable data models and staging/mart layers.
• Implement ELT workflows and optimize cloud data platforms.
• Create data quality tests and monitoring for pipelines.
• Collaborate with analytics, BI, and engineering to meet requirements.
• Tune data warehouse performance and query execution.
• Document pipelines using dbt documentation features.
• Support CI/CD and deployment automation for data pipelines.
• Troubleshoot data issues ensuring accuracy and reliability.

Skills

dbt (Data Build Tool)

SQL

Data Modeling

ELT/ETL

Cloud Platforms (AWS/Azure/GCP)

Data Warehousing

CI/CD

Git

Tools

Snowflake

BigQuery

Redshift

Synapse

Airflow

Prefect

Databricks

Spark

Terraform

Power BI

Tableau

Looker

Job description

Role & responsibilities

Job Title: Data Engineer (dbt)

Location: Gurgaon

Experience: 4-8 Years

Employment Type: Full-Time

Preferred candidate profile

Job Summary

We are seeking a talented Data Engineer (dbt) to design, build, and maintain scalable data transformation pipelines and analytics-ready data models. The ideal candidate will have hands-on experience with dbt (Data Build Tool), modern data warehouses, SQL, cloud platforms, and ELT frameworks. You will work closely with data architects, analysts, and business stakeholders to deliver reliable and high-quality data solutions.

Key Responsibilities

• Design, develop, and maintain data transformation pipelines using dbt.
• Build scalable and reusable data models following best practices.
• Develop and optimize ELT workflows within modern cloud data platforms.
• Create and maintain staging, intermediate, and mart-layer models.
• Implement data quality tests, validation rules, and monitoring frameworks.
• Collaborate with analytics, BI, and engineering teams to translate business requirements into data solutions.
• Optimize data warehouse performance and query execution.
• Develop and maintain documentation using dbt documentation features.
• Support CI/CD implementation and deployment automation for data pipelines.
• Troubleshoot data issues and ensure data accuracy, consistency, and reliability.

Required Skills

• Strong hands-on experience with dbt (Data Build Tool).
• Advanced proficiency in SQL and query optimization.
• Experience with modern data warehouses such as:
• Snowflake
• BigQuery
• Amazon Redshift
• Azure Synapse Analytics
• Strong understanding of ELT/ETL concepts and data transformation frameworks.
• Experience designing dimensional models, star schemas, and data marts.
• Knowledge of data warehousing and analytics engineering best practices.
• Experience with source control tools such as Git.
• Familiarity with CI/CD processes for data engineering workflows.
• Experience working with cloud platforms (AWS, Azure, or GCP).
• Strong troubleshooting and performance tuning skills.

Preferred Skills

• Experience with Airflow, Prefect, or other orchestration tools.
• Knowledge of Python for data engineering and automation.
• Experience with Databricks and Spark-based data platforms.
• Familiarity with data quality frameworks such as Great Expectations.
• Experience with Terraform and Infrastructure as Code (IaC).
• Exposure to Data Vault modeling concepts.
• Knowledge of BI tools such as Power BI, Tableau, or Looker.

Mandatory Skills

• dbt (Data Build Tool)
• SQL
• Data Modeling
• ELT/ETL
• Snowflake / BigQuery / Redshift / Synapse
• Git
• Cloud Platform (AWS/Azure/GCP)
• Data Warehousing
• CI/CD

Keywords for Sourcing

Data Engineer, Analytics Engineer, dbt Developer, dbt Core, dbt Cloud, SQL Developer, Snowflake, BigQuery, Redshift, Synapse, ELT, ETL, Data Modeling, Data Warehouse, Airflow, Python, Data Transformation, Analytics Engineering, Cloud Data Engineer, Modern Data Stack

Nice-to-Have Skills

• Airflow
• Python
• Databricks
• Spark
• Great Expectations
• Terraform
• Data Vault
• Power BI
• Tableau
• Looker

Ideal Candidate

A Data Engineer with 4+ years of data engineering experience and 2+ years of hands-on dbt experience, capable of building scalable, well-governed, analytics-ready data models and ELT pipelines in modern cloud data platforms.