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Data Engineer - SQL, Snowflake Jobs

161 Job Offers

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Expert Software Engineer - Data Orchestration
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Hong Kong
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Not provided
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Feedzai
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Staff Data Platform Engineer
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United States , San Francisco; New York City
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196000.00 - 294000.00 USD / Year
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Vercel
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Sales Engineer
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United States , San Francisco
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200000.00 - 250000.00 USD / Year
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Astronomer
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Head of Data, Automation & AI
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United Kingdom
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90000.00 GBP / Year
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Paragon Skills
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Senior Data Engineer
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Israel , TLV
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BioCatch
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Expert Software Engineer - Data Orchestration
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Australia , Sydney
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Feedzai
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Staff Data Platform Engineer
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United States , San Francisco; New York City
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196000.00 - 294000.00 USD / Year
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Vercel
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Expert Software Engineer - Data Orchestration
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Feedzai
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Senior Quantitative Data Engineer
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United States
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250000.00 USD / Year
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YipitData
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Senior Data Engineer
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Brazil
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Mindbody
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Data Architect
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United Kingdom; South Africa , London; Cape Town
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Collinson
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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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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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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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Machine Learning Operations Engineer
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United Kingdom , Richmond-Upon-Thames
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Retail Insight
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DataOps Engineer
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Hivex
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Technical Architect - Data
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India , Bengaluru
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EvoluteIQ
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AI/ML Engineer
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United States , New Jersey
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eGrove Systems
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Technical Project Manager
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Spain , Madrid
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Fever
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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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