INInfosys Limited
Snowflake Developer
Bangalore Posted 13 Oct 2026
FULL TIME
Data Modeling
snowflake
Git
Etl
Adf
+4 more
Job Description
Job Overview:
- We are looking for a skilled Snowflake DBT Developer with 5 to 8 years of experience in Data Engineering, Data Warehousing, and Cloud-based Analytics solutions.
- The ideal candidate will possess extensive knowledge in Snowflake, DBT (Data Build Tool), SQL, and both ETL and ELT development within cloud environments.
- This role involves designing, developing, optimizing, and maintaining robust data pipelines and analytics solutions.
Primary Duties:
- Main Responsibilities
- Design, develop, and sustain ELT/ETL pipelines utilizing Snowflake and dbt.
- Create and oversee dbt models, macros, snapshots, seeds, and incremental loading processes.
- Construct and enhance complex SQL queries tailored for large datasets.
- Execute data quality checks, testing, and documentation procedures using dbt.
- Leverage Snowflake features such as Snowpipe, Streams, Tasks, Cloning, and Time Travel.
- Develop and uphold dimensional data models, fact tables, and data marts.
- Conduct query optimization and warehouse enhancements in Snowflake.
- Collaborate effectively with business stakeholders and data engineering teams.
- Assist in deployment efforts through Git-based CI/CD practices.
- Essential Skills
- Proficient experience with Snowflake Data Warehouse.
- Hands-on expertise with dbt Core and dbt Cloud.
- Advanced skills in SQL programming and performance optimization.
- Familiarity with Data Modeling including Star Schema, Snowflake Schema, and Kimball methodologies.
- Understanding of ELT/ETL principles and pipeline creation.
- Experience with Cloud platforms such as AWS, Azure, and GCP.
- Knowledge of Git, CI/CD, and Agile practices.
- Experience with orchestration tools like Airflow, ADF, or Matillion.
Technical Skills:
- Technology Focus: Data on Cloud, DataStore, Snowflake, DBT.
Additional Qualifications:
- Preferred Qualifications
- Familiarity with Python or PySpark development.
- Exposure to Kafka and event-driven architecture.
- Experience with Databricks.
- Understanding of Machine Learning data pipelines.
- Knowledge of Data Mesh and Modern Data Stack concepts.
