Senior Snowflake Engineer

Accountabilities • Design, develop, and maintain scalable data pipelines and transformation solutions using Snowflake, including SnowSQL, Snowpark, Streams, Tasks, and Warehouses.

• Build and optimize complex SQL queries, stored procedures, UDFs, and transformation logic with a focus on performance and reliability.

• Develop data ingestion frameworks and integrations from APIs, files, SaaS platforms, cloud storage, and other sources.

• Design and implement data models using approaches such as 3NF, Data Vault, dimensional modeling, and star/snowflake schemas.

• Optimize Snowflake compute resources, warehouse sizing, caching strategies, and cost-performance tradeoffs.

• Establish and maintain data quality, lineage, observability, governance, and reliability across the pipeline lifecycle.

• Implement and improve CI/CD practices for data development, including version control, automated testing, and safe deployment processes.

• Integrate data platforms with BI tools and downstream consumers to support analytics and business reporting.

• Collaborate with technical project managers, client stakeholders, engineers, analysts, and product teams to clarify requirements, scope work, and align delivery timelines.

• Contribute to documentation, coding standards, reusable patterns, and engineering best practices across the data function.

• Work independently to identify blockers, solve complex technical challenges, and consistently deliver high-quality solutions.

Requirements

• 5+ years of professional experience in data engineering, including at least 2–3 years of hands-on Snowflake development.

• Advanced SQL expertise, including complex transformations, analytical functions, query optimization, and performance tuning.

• Strong hands-on experience with Snowflake capabilities such as Warehouses, RBAC, Streams, Tasks, Snowpipe, external stages, and data sharing.

• Experience with ETL/ELT tools and orchestration platforms such as dbt, Airflow, Azure Data Factory, AWS Glue, or Matillion.

• Experience designing data models for analytics and operational systems, including star schemas, snowflake schemas, and Data Vault.

• Strong understanding of data quality, governance, schema design, and data lifecycle management.

• Experience working with cloud data ecosystems across AWS, Azure, and/or GCP.

• Experience integrating Snowflake with BI platforms such as Tableau, Looker, or Power BI.

• Strong understanding of data pipeline reliability, testing, version control, and CI/CD practices.

• Clear and structured communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

• Strong sense of ownership, technical craftsmanship, accuracy, and reliability.

• Ability to work independently in a distributed, asynchronous environment and proactively communicate progress, risks, and blockers.

• Comfort working with evolving requirements and adapting solutions as project priorities change.

Benefits

• Fully remote work model.

• Remote-first environment with the option to work from a coworking space or office where available.

• Flexible approach focused on outcomes rather than hours worked.

• Asynchronous collaboration designed to respect different time zones and working styles.

• Opportunity to work on varied projects across areas such as healthcare, commerce, sustainability, and emerging technology.

• Collaboration with an international team of experienced engineers and technology professionals.

• Opportunities for professional growth, skill development, and increased responsibility.

• Culture focused on continuous improvement, high-quality engineering, thoughtful feedback, and sustainable delivery.

• Exposure to technically challenging data engineering projects and modern cloud data ecosystems.

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