Snowflake + DBT Developer

Job Title:
Snowflake + DBT Developer

Location:
Hyderabad

Experience:
4+ years

Job Type:
Full-Time

Department:
Enterprise Data and Analytics

About The Role
We are looking for an experienced
Snowflake + DBT Developer
to join our
Technology Team .
This role demands a deep understanding of data pipeline migration, modeling, and orchestration using modern data stack technologies like
Snowflake, DBT, Databricks
, and
Airflow
. You will play a crucial role in
migrating existing pipelines from Databricks to Snowflake
, building scalable and performant workflows, and ensuring seamless data integration and delivery across environments.

This is a highly collaborative role requiring strong communication skills and hands-on experience with
CI/CD, orchestration, monitoring
, and
modern data engineering best practices
.

Key Responsibilities
Migration & Architecture
Analyze and understand existing data pipelines built using Databricks (PySpark/Spark).

Re-architect and rebuild pipelines for Snowflake using SQL-based transformations and DBT models.

Ensure high performance, scalability, and data consistency during and post-migration.

Snowflake Development
Develop using Snowflake-native features: Snowpipe, Streams/Tasks, Dynamic Tables, Materialized Views, Secured Views, RBAC, Data Masking, Row-Level Security, etc.

Implement performance tuning, query optimization, and cost-effective warehouse management.

Leverage metadata layers, query history, and account usage for monitoring and auditing.

DBT (Data Build Tool)
Build and manage modular DBT models, macros, and materializations.

Maintain version-controlled environments and promote changes across Dev → Test → Prod using CI/CD.

Ensure documentation, testing, and validation within DBT framework.

Workflow Orchestration & Automation
Design, build, and manage Airflow DAGs for end-to-end orchestration

Integrate orchestration with tools such as Cosmos, Astronomer, or Docker.

DevOps & CI/CD
Create and manage automated deployment pipelines using GitHub Actions, Azure DevOps, or similar.

Enforce coding standards, peer reviews, and Git-based version control.

Monitoring & Alerting
Implement proactive monitoring, logging, and alerting mechanisms for data pipelines.

Develop self-healing or alert-driven systems to address critical failures or anomalies.

Technical Requirements
4+ years of experience in data engineering with strong hands-on experience in Snowflake and DBT.

Proven experience in Databricks (PySpark/Spark) and migrating workloads to Snowflake.

Strong Understanding Of
RBAC, Data Sharing, Database Replication, Stored Procedures, Snowpipe vs Streams, Authentication (MFA).

Dynamic Tables vs Materialized Views, Secured Views, Query Optimization, Pruning, Meta Data, and Query History.

Proficiency in SQL development, data modeling, and performance tuning in Snowflake.

Experience with orchestration tools like Airflow and containerized deployments using Docker.

Familiarity with CI/CD pipelines, code versioning, and deployment automation.

Knowledge of data governance, security controls, and masking techniques.

Nice-to-Have
Experience with Headless BI Tools or Data Visualization Platforms.

Familiarity with Cloud Services (AWS/Azure/GCP) and deployment on platforms like Snowflake on AWS/Azure.

Exposure to i18n/localization in data products or multi-tenant data platforms.

Soft Skills
Strong analytical thinking and attention to detail.

Excellent verbal and written communication skills.

Ability to work independently as well as collaboratively across cross-functional teams.

Self-driven, proactive, and capable of managing multiple tasks simultaneously.

Willingness to mentor peers and contribute to process improvement and documentation.