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Snowflake data engineer Jobs

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Senior Software Engineer – GTM Systems
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Ireland , Dublin
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Not provided
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Intercom
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Senior Software Engineer – GTM Systems
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United States , Chicago
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185000.00 - 220000.00 USD / Year
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Intercom
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Lead Product Manager, Data & A.I
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176000.00 - 289800.00 USD / Year
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Velocity Global
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Lead Product Manager, Data & A.I
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United States , Palo Alto
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176000.00 - 289800.00 USD / Year
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Velocity Global
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Head of Business Analytics
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United States
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174000.00 - 270000.00 USD / Year
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Anaconda
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Data Architect
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India , Noida
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3Pillar Global
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Data Architect
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Canada
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3Pillar Global
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Enterprise Data Architect
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United States , San Mateo
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200000.00 - 275000.00 USD / Year
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Verkada
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Senior Crypto Backend Engineer
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Token Metrics
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Principal Data Architect
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United States; Canada
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170000.00 - 200000.00 USD / Year
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Terazo
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Delivery Director
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United Kingdom , Bristol
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110000.00 - 140000.00 GBP / Year
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Snap Analytics
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Senior Data Science Solution Architect
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United States , Irving
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Hire IT People, Inc
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Founding Technical ISV Alliance Lead
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United States
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190000.00 - 230000.00 USD / Year
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Hightouch
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Senior ThoughtSpot Engineer
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United States
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115000.00 - 175000.00 USD / Year
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Hike2
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Technical Architect - Data
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India , Bengaluru
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EvoluteIQ
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Full-Stack JavaScript Developer
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Poland
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Ascendix Tech
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Full-Stack JavaScript Developer
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Portugal
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Ascendix Tech
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Analytics Engineer, Product Analytics
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United States , San Francisco; New York City
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143600.00 - 177200.00 USD / Year
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Airtable
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Technical Project Manager
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Spain , Madrid
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Fever
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Senior Manager Analytics
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Norway , Oslo
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Circle K
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A Snowflake Data Engineer is a specialized professional at the forefront of modern cloud data management, focusing on designing, building, and maintaining scalable data infrastructure within the Snowflake Data Cloud. This role is central to transforming raw, disparate data into a trusted, organized, and high-performance asset that drives analytics and business intelligence. As organizations increasingly migrate to cloud-native platforms, the demand for skilled Snowflake Data Engineer jobs continues to surge, offering lucrative and impactful career opportunities for those with the right expertise. Typically, professionals in this role manage the end-to-end data lifecycle. This begins with ingesting data from various sources—such as transactional databases, SaaS applications, and IoT streams—into Snowflake. They then design and implement robust, automated data pipelines using tools like Snowpipe, dbt (data build tool), and orchestration frameworks (e.g., Apache Airflow, Prefect). A core responsibility is data modeling, where they structure data efficiently using dimensional models (star and snowflake schemas) or other paradigms to optimize for analytical query performance and business user understanding. Ensuring data quality, implementing governance policies, and maintaining security and access controls are also fundamental daily tasks. The skill set for these jobs is a blend of deep platform-specific knowledge and broader data engineering principles. Proficiency in SQL is paramount, given Snowflake's SQL-centric architecture. Engineers must understand Snowflake's unique architecture, including virtual warehouses, clustering keys, and data sharing capabilities. Often, familiarity with programming languages like Python is required for scripting and advanced transformations. Knowledge of version control (Git), CI/CD practices, and cloud ecosystem tools (AWS, Azure, GCP) is highly valued. While certifications like SnowPro Core are a common benchmark, practical experience in building scalable pipelines and a solid grasp of data warehousing concepts are the true cornerstones of the role. Ultimately, a Snowflake Data Engineer acts as a crucial bridge between raw data and business insight. They empower data analysts, scientists, and business stakeholders by providing a single source of truth, enabling data-driven decision-making across the organization. For individuals passionate about cloud technologies, data architecture, and solving complex data challenges, pursuing Snowflake Data Engineer jobs represents a strategic career path in the evolving data landscape.

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