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Data Engineer - SQL, Snowflake Jobs

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Data Engineering Manager
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United States , Austin
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Arrive Logistics
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Senior Vice President, Data & Analytics Engineering
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United States , Boston
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315000.00 - 365000.00 USD / Year
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Berkshire Hathaway Specialty Insurance
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Data Engineer
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Sweden , Stockholm
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Stegra
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Senior Data Engineer (Graph)
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United States , San Francisco
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90.00 - 93.00 USD / Hour
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Software Resources
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Technical Project Manager - Data Team
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Spain , Barcelona; Madrid
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Fever
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Data Project Manager
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Argentina , Buenos Aires
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Fever
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DevOps Engineer
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Israel , TLV
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BioCatch
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Technical Lead – AI/ML & Data Platforms
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United States , Sunnyvale
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Thirdeye Data
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Director, Data Operations
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United States , New York; Oakland
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177000.00 - 234000.00 USD / Year
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SiriusXM
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Senior Staff Software Engineer
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United States , New York
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156400.00 - 225000.00 USD / Year
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SiriusXM
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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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Solution Engineer
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United Kingdom , London
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Sigma Computing
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Head of Data & AI
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United Kingdom , London
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Orbis Consultants
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Data Architect
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United Kingdom , London
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myGwork - LGBTQ+ Business Community
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Pre-Sales Solution Engineer
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LakeFS
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Senior Sales Engineer
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United States
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Infinite Lambda
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Senior Privacy Engineer
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United States , San Francisco
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156000.00 - 234000.00 USD / Year
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GoFundMe
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Product Manager - Data
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India , Bengaluru
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EvoluteIQ
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Senior Data Architect
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India , Noida; Chennai; Bangalore
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Sopra Steria
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Director Engineering- Security Service Edge (SSE)
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Israel , Tel Aviv
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Hewlett Packard Enterprise
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Explore Data Engineer jobs focused on SQL and Snowflake, a dynamic career path at the heart of modern data-driven organizations. Data Engineers are the architects and builders of robust data infrastructure, responsible for designing, constructing, and maintaining the systems that transform raw data into reliable, accessible information for analytics and business intelligence. Professionals in these roles are pivotal in enabling data scientists, analysts, and business leaders to make informed decisions by ensuring data is clean, structured, and available. A Data Engineer specializing in SQL and Snowflake typically designs and implements scalable data warehouses and data lakes within the Snowflake cloud platform. Their core mission is to build efficient, automated data pipelines that ingest data from diverse sources—such as databases, applications, and APIs—and transform it into a usable format. Common responsibilities include writing complex SQL queries for data transformation and analysis, optimizing Snowflake environments for performance and cost, and developing ETL (Extract, Transform, Load) or ELT processes. They also ensure data quality, implement security and governance policies like access controls, and collaborate with other teams to understand data requirements and deliver reliable data models. The typical skill set for these jobs is a blend of deep technical expertise and analytical problem-solving. Proficiency in advanced SQL is fundamental, as it is the primary language for manipulating data within Snowflake. Hands-on experience with the Snowflake platform itself—including features like virtual warehouses, data sharing, Snowpipe, and Snowpark—is highly sought after. Strong scripting skills, particularly in Python, are common for building data pipelines, automating tasks, and handling API integrations. A solid understanding of cloud platforms (AWS, Azure, or GCP) and their data services is often expected, as Snowflake is frequently integrated within these ecosystems. Familiarity with modern data orchestration tools (like Apache Airflow), transformation tools (like dbt), and CI/CD practices is increasingly valuable. Beyond technical skills, successful candidates possess strong communication abilities to bridge technical and business domains, a keen eye for data governance, and a commitment to building secure, efficient, and well-documented data solutions. For those seeking Data Engineer - SQL, Snowflake jobs, this profession offers the opportunity to work on cutting-edge data technology, solving complex challenges of scale and complexity. It is a role that demands continuous learning and adaptation as the data landscape evolves, making it a rewarding and future-proof career choice for technically minded individuals passionate about building the foundational systems that power insight and innovation.

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