Data Engineer: DBT specific

Data Engineer Requirement

Hello Team,

Reaching out to you for the requirement of Data Engineer 7 + years experience,

No GAP in work history of 7 years relevant experience. BGV will be required or

will have to be done for the candidate. This is a remote opportunity and hence

bench resources are to be invited for the interview for this position. The

opening is for 2 candidates.

Kindly, submit 2 profiles from your end which fit the criteria mentioned above

and has the following expertise in the data engineering domain.

Data Engineer

•

Lead the end-to-end technical design and execution of migration from

Snowflake/Glue to DBT.

•

Define and govern the data architecture across landing, bronze, silver, and

gold layers on DBT.

•

Translate business and source system logic into modular, well-documented DBT

models.

•

Guide Python-based ETL pipeline development and ensure output parity with

legacy Snowflake pipelines.

•

Drive technical decisions on partitioning, optimization, and performance

tuning in Spark/DBT.

•

Collaborate with client architects, data stewards, and QA teams to validate

migration fidelity.

•

Mentor and technically review work from India-based Data Engineers.

•

Facilitate sprint planning, technical reviews, and architecture walkthroughs

with client stakeholders.

•

Proactively identify scope risks, dependencies, and technical blockers and

communicate remediation plans.

•

Ensure compliance with data governance, security, and access control

standards.

Key Responsibilities

•

Design, develop, and maintain modular DBT models following industry best

practices.

•

Build scalable transformation pipelines using DBT Core or DBT Cloud.

•

Convert complex business requirements into reusable SQL models.

•

Develop incremental models, snapshots, seeds, and macros.

•

Create and maintain DBT source configurations and model documentation.

•

Implement comprehensive data quality tests using built-in and custom DBT

tests.

•

Optimize model execution performance and dependency management.

•

Design dimensional models including facts, dimensions, and aggregate tables.

•

Implement Medallion Architecture (Bronze, Silver, Gold) using DBT

transformations.

•

Perform query optimization and improve warehouse performance.

•

Participate in code reviews and enforce DBT development standards.

•

Collaborate with Data Engineers, Data Architects, BI Developers, and

Business Analysts.

•

Support CI/CD deployment pipelines for DBT projects.

•

Troubleshoot production issues and resolve data pipeline failures.

Core DBT Skills

•

DBT Core / DBT Cloud (3+ Years)

•

Advanced DBT Model Development

•

Incremental Models

• Snapshots
• Seeds

•

Macros & Jinja Templates

•

Source Configuration

•

Model Documentation

•

Data Lineage Management

•

Package Management

•

Custom DBT Tests

•

Schema.yml Configuration

•

Project Structure & Best Practices

SQL & Data Transformation

•

Advanced SQL (4+ Years)

• Complex Joins

•

Common Table Expressions (CTEs)

•

Window Functions

•

Stored Procedures (Preferred)

•

Query Optimization

•

Execution Plan Analysis

•

Data Cleansing & Transformation

Data Modeling

•

Dimensional Data Modeling

• Star Schema

•

Snowflake Schema

•

Fact & Dimension Tables

•

Slowly Changing Dimensions (SCD Type 1 & 2)

•

Data Vault (Preferred)

•

Medallion Architecture

Cloud Data Warehousing

Hands-on experience with one or more

• Snowflake

•

Databricks SQL Warehouse

• Google BigQuery
• Amazon Redshift

•

Azure Synapse Analytics

Data Quality & Governance

• Data Validation

•

Data Quality Frameworks

• DBT Tests

•

Source Freshness Checks

•

Schema Enforcement

•

Metadata Management

• Data Lineage

•

Documentation Standards

CI/CD & DevOps

• Git

•

GitHub / GitLab / Azure DevOps

• CI/CD Pipelines

•

Environment Management (Dev, QA, Prod)

•

Version Control Best Practices

•

Deployment Automation

Preferred Technical Skills

•

Python (Good to Have)

• Apache Airflow

•

Apache Spark (Preferred)

• Snowflake
• Databricks

•

AWS / Azure / GCP Exposure

• REST APIs

Soft Skills

•

Strong Analytical Thinking

• Problem Solving

•

Excellent SQL Debugging Skills

•

Technical Documentation

•

Cross-functional Collaboration

•

Code Review & Mentoring

Preferred Qualifications

•

Bachelor's degree in Computer Science, Engineering, Information Technology,

or related field.

•

Experience with modern ELT architectures.

•

Hands-on experience with DBT Cloud deployment workflows.

•

Familiarity with Agile/Scrum methodologies.

Nice to Have

•

Experience migrating legacy ETL pipelines to DBT.

•

Knowledge of Apache Airflow or Azure Data Factory orchestration.

•

Experience with BI tools such as Power BI, Tableau, or Looker.

•

Exposure to data observability tools like Great Expectations or Monte Carlo.

This document is for internal use only. Please maintain confidentiality.