Snowflake & DBT Data Engineer

Job description

Location- Bangalore

Experience- 5-8 Yrs

Overview :

We are seeking a highly skilled

Data Engineer

with strong hands-on experience in

Snowflake

and

dbt (Data Build Tool)

to join our data engineering team. The ideal candidate will be responsible for designing and developing scalable data pipelines, performing advanced data transformations, and ensuring data quality using modern data stack technologies.

Key Responsibilities :

Design, develop, and optimize data pipelines using

dbt

and

Snowflake .

Build efficient, reliable, and scalable data transformation models with

dbt Core or dbt Cloud .

Implement Snowflake features such as

Snowpipe, Streams, Tasks, and Dynamic Tables .

Work closely with Data Analysts and Analytics Engineers, and Business teams to understand data requirements.

Ensure data quality and perform rigorous

data testing and validation

using

dbt tests .

Maintain and enhance the

data warehouse architecture

to support business intelligence and reporting needs.

Monitor data pipeline performance and troubleshoot issues proactively.

Apply

version control practices (Git)

and CI / CD for data workflows.

Strong proficiency in Python. The resource should be comfortable writing production-grade Python code, interacting with APIs to extract and integrate data from various sources, and automating workflows.

Experience with handling large-scale data ingestion, transformation, and processing tasks, ensuring data quality, reliability, and scalability across platforms.

Required Skills & Qualifications :

5+ years of experience in Data Engineering.

Strong hands-on experience with

Snowflake

– including data modeling, performance tuning, and administration.

Advanced proficiency in

dbt

(Core or Cloud) for data transformations and testing.

Proficient in

SQL

(complex queries, CTEs, window functions, optimization).

Experience with

ETL / ELT design patterns

and tools like Apache Nifi, Airflow, and Fivetran.

Solid understanding of

data warehousing concepts, dimensional modeling,

and

medallion architecture.

Experience with AWS

Cloud Platforms

is a must OR experience with other cloud service providers like Azure, or GCP is a plus.

Familiarity with

Git / GitHub

and version-controlled deployment pipelines.

Excellent communication skills and ability to work in cross-functional teams.

Demonstrated ability to thrive in fast-paced environments. The resource should have a strong aptitude to be comfortable diving deep into datasets, identifying patterns, and uncovering data quality issues in environments where data sanity is low.