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.