[Hiring] Snowflake Data Engineer @NewVison

Role Description

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
• Cloud-native data ecosystems

This role will work closely with:

• Data engineers
• Architects
• Analytics teams
• Business stakeholders
• DevOps
• Application teams

Key responsibilities include:

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

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.