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Senior Data Engineer

🕒 June 10

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Trulieve

5001 - 10000 employees

Founded 2016

👥 B2C

⚕️ Healthcare Insurance

💊 Pharmaceuticals

B2C • Healthcare Insurance • Pharmaceuticals

Trulieve is a fast expanding cannabis organization dedicated to helping patients regain their quality of life through medicinal and recreational marijuana. The company prides itself on diversity, social responsibility, and innovation within the cannabis industry, and offers various career opportunities across corporate, production, and retail sectors.

📋 Description

• Design and Implement Snowflake-Native Data Architectures • Lead the creation and optimization of modern data architectures on Snowflake • Ensure that the architecture supports high-volume data workloads, near-real-time freshness requirements, and integrates seamlessly with upstream operational systems and downstream analytics consumers. • Lead the Development of Complex, End-to-End Data Pipelines Using Native Snowflake Services • Architect and build data pipelines using Dynamic Tables for declarative SQL-based transformations with automated dependency management and incremental refresh. • Implement real-time and near-real-time ingestion using Snowpipe and Snowpipe Streaming.

🎯 Requirements

• 7+ years of experience in data engineering or related fields • Deep Understanding of Data Engineering Concepts • Extensive knowledge of data modeling, including designing and maintaining relational, dimensional, and semi-structured data models within Snowflake. • Proficiency in data warehousing concepts with hands-on experience designing multi-layer transformation pipelines (staging, intermediate, marts). • Strong understanding of incremental processing patterns, change data capture (CDC), and slowly changing dimension (SCD) strategies. • Expertise in Snowflake Platform and Native Data Pipeline Services • Deep proficiency with Snowflake Dynamic Tables (TARGET_LAG, REFRESH_MODE, pipeline dependency graphs, incremental vs. full refresh). • Hands-on experience with Snowpipe and Snowpipe Streaming for continuous and real-time data ingestion. • Strong knowledge of Snowflake Streams and Tasks for event-driven and procedural pipeline orchestration. • Experience with Snowpark (Python/Scala) for complex data transformations and UDFs/UDTFs. • Familiarity with Snowflake Cortex AI functions for embedding AI/ML capabilities into data pipelines. • Proficiency in SQL, Python, and Data Engineering Frameworks • Advanced SQL skills including window functions, CTEs, recursive queries, semi-structured data handling (VARIANT, OBJECT, ARRAY), and performance optimization. • Python proficiency for Snowpark development, automation scripting, and integration work. • Experience with modular SQL transformation development, testing, and documentation using native Snowflake patterns and shared engineering standards. • Familiarity with orchestration platforms such as Apache Airflow / Astronomer for pipeline scheduling and monitoring. • Hands-on experience designing solutions for real-time and near-real-time data pipelines using Snowpipe Streaming and Kafka connectors. • Strong Knowledge of Cloud Infrastructure and Cost Optimization • Expertise in cloud platforms (AWS, Azure, or GCP) with a focus on integration with Snowflake (external stages, storage integrations, PrivateLink). • Experience with Snowflake cost management including warehouse sizing strategies, auto-suspend/resume, resource monitors, and query optimization. • Familiarity with infrastructure-as-code tools (Terraform, Pulumi) for managing Snowflake resources declaratively

🏖️ Benefits

• A comprehensive benefits package including paid time off

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