Data Engineer

We are seeking an experienced Data Engineer - Snowflake to design, build, and maintain scalable data pipelines and cloud data solutions. The ideal candidate will have strong hands-on experience with Snowflake, SQL, Python, ETL/ELT, data modelling, and cloud data platforms.

The Data Engineer will work closely with data analysts, data scientists, software engineers, and business stakeholders to build reliable data products and transform raw data into high-quality, analytics-ready datasets.

Snowflake supports modern data engineering workflows using SQL, Python/Snowpark, dbt, tasks, streams, and other capabilities for building and orchestrating data pipelines., * Design, develop, and maintain scalable data pipelines using Snowflake.

• Build robust ETL/ELT processes for batch and near-real-time data ingestion.
• Develop complex SQL queries, stored procedures, views, and data transformations.
• Use Snowpark Python to build scalable data processing and transformation workflows.
• Develop and maintain data models for analytics, reporting, and downstream applications.
• Implement incremental data processing using Snowflake Streams, Tasks, Dynamic Tables, or equivalent technologies.
• Integrate data from APIs, databases, cloud storage, SaaS applications, and enterprise systems.
• Develop data ingestion pipelines from platforms such as AWS S3, Azure Data Lake, or other cloud storage systems.
• Optimize Snowflake queries, warehouses, tables, and pipelines for performance and cost.
• Implement data quality checks, validation, monitoring, and error handling.
• Support data governance, security, access controls, and data lifecycle management.
• Work with dbt to develop modular, tested, and maintainable transformation pipelines.
• Build CI/CD processes for data engineering code and Snowflake deployments.
• Troubleshoot production data pipelines and resolve data quality or performance issues.
• Collaborate with analysts and business stakeholders to understand data requirements.
• Document data architecture, pipeline workflows, data models, and technical processes.
• Participate in Agile ceremonies, code reviews, technical design discussions, and sprint planning.

• 4+ years of experience in data engineering or a related technical role.
• 2+ years of hands-on experience with Snowflake.
• Strong proficiency in SQL.
• Strong programming experience with Python.
• Experience developing enterprise-scale ETL/ELT data pipelines.
• Strong understanding of data warehousing concepts and dimensional data modeling.
• Experience with Snowflake objects including databases, schemas, tables, views, stages, warehouses, tasks, and streams.
• Experience working with structured and semi-structured data such as JSON, Parquet, and CSV.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Git and software development best practices.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience with Snowpark Python.
• Experience with dbt and dbt Cloud.
• Experience with Apache Airflow or another workflow orchestration platform.
• Experience with Kafka, Kinesis, or other streaming technologies.
• Experience with AWS S3, Azure Data Lake Storage, or Google Cloud Storage.
• Experience with Terraform or Infrastructure as Code.
• Familiarity with CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
• Experience with data quality and observability platforms.
• Knowledge of cloud security, encryption, IAM, and data governance.
• Experience working with large-scale enterprise data environments.

Snowflake’s current data engineering capabilities include Snowpark for Python, SQL-based transformations, dbt Projects, Tasks, Streams, and CI/CD-oriented development workflows.