Listed on Himalayas. You apply through their page. We never charge applicants.
Estimated pay
Estimate$162K–$279K/yr
Estimate — the employer hasn't published pay.
Based on 260 similar mid-level Data Science & ML jobs in United States that show pay. The range is the middle half of their posted pay (25th to 75th percentile), not an offer — ask the employer for the real range.
Data Science & ML salaries →Prepare for this job
Free on every jobLikely interview questions
At a glance
- Education
- Master's
Skills mentioned
About the role
This is a remote position.
Snowflake Engineer
Experience: 1–3 Years
Location: Hyderabad / Remote
Employment Type: Full-time About the Role
We are looking for a Snowflake Engineer with 1–3 years of hands-on experience in data engineering and cloud data platforms. The ideal candidate should have practical experience working with Snowflake, SQL, Python, and ETL/ELT pipelines and be comfortable working with large datasets.
This role is suited for someone who enjoys solving data problems, learning new technologies, and building scalable data solutions.
Key Responsibilities
- Develop and maintain data pipelines using Snowflake and SQL.
- Write complex SQL queries for data transformation, extraction, and analysis.
- Build and maintain ETL/ELT pipelines from multiple data sources.
- Work with Snowflake features such as Streams, Tasks, Snow pipe, and stored procedures.
- Develop data transformations and automation using Python.
- Create and maintain tables, views, schemas, and data models in Snowflake.
- Monitor and troubleshoot data pipelines and resolve data quality issues.
- Optimize SQL queries and Snowflake workloads for performance and cost.
- Work with cloud storage and services such as AWS S3, Azure Blob Storage, or GCP.
- Collaborate with senior engineers, analysts, and other stakeholders to understand data requirements.
- Participate in code reviews, testing, deployment, and technical documentation.
- Follow best practices for data security, quality, and reliability.
Required Skills
-
1–3 years of hands-on experience in Data Engineering, Data Warehousing, or a related role.
- Hands-on experience with Snowflake.
- Strong SQL skills.
- Working knowledge of Python.
- Understanding of ETL/ELT pipelines and data integration.
- Basic understanding of data modelling and database concepts.
- Experience working with at least one cloud platform — AWS, Azure, or GCP.
- Familiarity with Git/version control.
- Good analytical and problem-solving skills.
Requirements
Good to Have
- Experience with Snowflake Streams, Tasks, Snow pipe, or Dynamic Tables.
- Experience with dbt.
- Familiarity with Apache Airflow or other workflow orchestration tools.
- Exposure to AWS services such as S3, Lambda, Glue, or Redshift.
- Experience with APIs, JSON, or other data formats.
- Exposure to CI/CD practices.
- Understanding of data quality and data governance.
- Snowflake certification.
What We're Looking For
- Strong hands-on and practical approach to problem-solving.
- Ability to understand requirements and translate them into technical solutions.
- Good communication and collaboration skills.
- Willingness to learn and work with modern data technologies.
- Ability to work independently while collaborating with senior team members.
- Strong attention to detail and data quality.
About the Role
We are looking for a Snowflake Engineer with 1–3 years of hands-on experience in data engineering and cloud data platforms. The ideal candidate should have practical experience working with Snowflake, SQL, Python, and ETL/ELT pipelines and be comfortable working with large datasets.
This role is suited for someone who enjoys solving data problems, learning new technologies, and building scalable data solutions.
Key Responsibilities
- Develop and maintain data pipelines using Snowflake and SQL.
- Write complex SQL queries for data transformation, extraction, and analysis.
- Build and maintain ETL/ELT pipelines from multiple data sources.
- Work with Snowflake features such as Streams, Tasks, Snow pipe, and stored procedures.
- Develop data transformations and automation using Python.
- Create and maintain tables, views, schemas, and data models in Snowflake.
- Monitor and troubleshoot data pipelines and resolve data quality issues.
- Optimize SQL queries and Snowflake workloads for performance and cost.
- Work with cloud storage and services such as AWS S3, Azure Blob Storage, or GCP.
- Collaborate with senior engineers, analysts, and other stakeholders to understand data requirements.
- Participate in code reviews, testing, deployment, and technical documentation.
- Follow best practices for data security, quality, and reliability.
Required Skills
-
1–3 years of hands-on experience in Data Engineering, Data Warehousing, or a related role.
- Hands-on experience with Snowflake.
- Strong SQL skills.
- Working knowledge of Python.
- Understanding of ETL/ELT pipelines and data integration.
- Basic understanding of data modelling and database concepts.
- Experience working with at least one cloud platform — AWS, Azure, or GCP.
- Familiarity with Git/version control.
- Good analytical and problem-solving skills.
Requirements
Good to Have
- Experience with Snowflake Streams, Tasks, Snow pipe, or Dynamic Tables.
- Experience with dbt.
- Familiarity with Apache Airflow or other workflow orchestration tools.
- Exposure to AWS services such as S3, Lambda, Glue, or Redshift.
- Experience with APIs, JSON, or other data formats.
- Exposure to CI/CD practices.
- Understanding of data quality and data governance.
- Snowflake certification.
What We're Looking For
- Strong hands-on and practical approach to problem-solving.
- Ability to understand requirements and translate them into technical solutions.
- Good communication and collaboration skills.
- Willingness to learn and work with modern data technologies.
- Ability to work independently while collaborating with senior team members.
- Strong attention to detail and data quality.
Originally posted on Himalayas