Senior Snowflake Engineer
- Role
- Data Engineering
- Experience
- Senior
- Employment
- Full-time
Open to IN only. Set where you work from to check your eligibility.
No BS summary
Senior Data Engineer with 4–8 years in data engineering. Must have strong Python, Matillion, Snowflake, SQL, ETL/ELT, data warehousing, and cloud platform experience. Role is based in Hyderabad, India.
Core skills
Required skills
Optional skills
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients.
We are looking for an experienced Senior Data Engineer with strong expertise in Python, Matillion, and Snowflake to design, develop, and optimize scalable data pipelines and cloud-based data warehouse solutions. The ideal candidate should have hands-on experience in ETL/ELT development, data modeling, and cloud data engineering while working in an agile environment. Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines using Matillion . Build and optimize data warehouse solutions on Snowflake . Develop robust data processing frameworks and automation scripts using Python . Create and maintain data models, transformations, and workflows to support business analytics. Optimize Snowflake performance, including query tuning, clustering, and warehouse management. Integrate data from multiple structured and unstructured sources. Collaborate with business stakeholders, analysts, and cross-functional engineering teams to deliver high-quality data solutions. Implement data quality, validation, monitoring, and error-handling mechanisms. Participate in code reviews, testing, deployment, and production support activities. Follow best practices for security, governance, and documentation.
4 to 8 years of experience in Data Engineering. Strong hands-on experience with Python , Matillion , and Snowflake . Experience building ETL/ELT pipelines and data integration solutions. Strong SQL skills with experience in query optimization. Good understanding of data warehousing concepts and dimensional data modeling. Experience working with cloud platforms such as AWS , Azure , or GCP . Knowledge of Git, CI/CD pipelines, and Agile methodologies. Strong analytical, troubleshooting, and problem-solving s
Experience with orchestration tools such as Airflow. Exposure to DBT is an added advantage. Knowledge of REST APIs and data integration techniques. Familiarity with data governance and security best practices.
What you'll do
- Design, develop, and maintain scalable ETL/ELT pipelines using Matillion.
- Build and optimize data warehouse solutions on Snowflake.
- Develop robust data processing frameworks and automation scripts using Python.
- Create and maintain data models, transformations, and workflows to support business analytics.
- Optimize Snowflake performance, including query tuning, clustering, and warehouse management.
- Integrate data from multiple structured and unstructured sources.
- Collaborate with business stakeholders, analysts, and cross-functional engineering teams to deliver high-quality data solutions.
- Implement data quality, validation, monitoring, and error-handling mechanisms.
- Participate in code reviews, testing, deployment, and production support activities.
- Follow best practices for security, governance, and documentation.
What they require
- 4 to 8 years of experience in Data Engineering.
- Strong hands-on experience with Python, Matillion, and Snowflake.
- Experience building ETL/ELT pipelines and data integration solutions.
- Strong SQL skills with experience in query optimization.
- Good understanding of data warehousing concepts and dimensional data modeling.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of Git, CI/CD pipelines, and Agile methodologies.
- Strong analytical, troubleshooting, and problem-solving skills.
- Preferred: Experience with orchestration tools such as Airflow.
- Preferred: Exposure to DBT is an added advantage.
- Preferred: Knowledge of REST APIs and data integration techniques.
- Preferred: Familiarity with data governance and security best practices.
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