Snowflake Data Engineer

Job Summary

We are seeking an experienced Snowflake Data Engineer to design, build, optimize, and manage scalable enterprise data platforms using Snowflake and modern cloud data technologies. The ideal candidate will have strong expertise in data architecture, data engineering, Snowflake development, ETL/ELT pipelines, data modeling, performance optimization, and cloud-native data ecosystems.

This role will work closely with data engineers, architects, analytics teams, business stakeholders, DevOps, and application teams to develop secure, reliable, and high-performing data solutions that support business intelligence, analytics, reporting, and advanced data initiatives.

Key Responsibilities

• Design and develop enterprise-scale data architectures using Snowflake and modern cloud data platforms.
• Build scalable and reliable ETL/ELT data pipelines for batch and near-real-time data processing.
• Develop and optimize Snowflake databases, schemas, tables, views, stored procedures, tasks, streams, and stages.
• Design effective data models, including dimensional, normalized, denormalized, and analytical models.
• Develop data ingestion frameworks to integrate data from databases, APIs, applications, files, and third-party systems.
• Implement Snowflake features such as Streams, Tasks, Snowpipe, Dynamic Tables, Time Travel, Zero-Copy Cloning, and Secure Data Sharing.
• Optimize Snowflake workloads for performance, scalability, concurrency, and cost efficiency.
• Analyze query performance and implement appropriate clustering, partitioning, warehouse sizing, caching, and SQL optimization strategies.
• Develop reusable data engineering frameworks and standards for enterprise data solutions.
• Design and implement data lake, data warehouse, and lakehouse architectures where applicable.
• Implement data security, governance, access controls, encryption, masking, row-level security, and data-sharing strategies.
• Work with cloud platforms such as AWS, Azure, or Google Cloud Platform to integrate Snowflake with broader cloud data ecosystems.
• Build and maintain CI/CD pipelines for data engineering and Snowflake deployments.
• Collaborate with DevOps teams to implement infrastructure automation and deployment processes.
• Establish data quality, validation, monitoring, and observability frameworks.
• Troubleshoot data pipeline failures, performance issues, data inconsistencies, and production incidents.
• Develop technical documentation covering architecture, data flows, data models, integration patterns, and operational procedures.
• Mentor data engineers and provide technical leadership on Snowflake and cloud data engineering initiatives.
• Evaluate new Snowflake capabilities, cloud technologies, and data engineering tools to continuously improve the platform.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
• 8+ years of experience in data engineering, data architecture, database development, or related areas.
• 4+ years of hands-on experience with Snowflake in enterprise environments.
• Strong experience designing and implementing cloud-based data warehouse architectures.
• Advanced SQL development and query optimization skills.
• Strong experience with Snowflake architecture, performance tuning, security, and cost optimization.
• Hands-on experience building enterprise ETL/ELT pipelines.
• Strong knowledge of data modeling, dimensional modeling, star/snowflake schemas, and data warehouse design.
• Experience with Python and/or other programming languages used for data engineering.
• Experience with orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or similar technologies.
• Strong understanding of cloud platforms, preferably AWS, Azure, or GCP.
• Experience with Git-based version control and CI/CD practices.
• Strong understanding of data governance, security, data quality, and metadata management.
• Experience working with large-scale and complex datasets.