Snowflake & DBT Data Engineer

1 day ago

Bengaluru, India Scientist Technologies Full time

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. 


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