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Data Engineer - Python and Spark Jobs

139 Job Offers

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Palantir Data Engineer
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Romania
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Airswift Sweden
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Lead Data Engineer
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United States
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Rearc
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Big Data Engineer
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United States , St. Louis
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Protocol Infotech
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Principal Data Engineer
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United States
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183200.00 - 203500.00 USD / Year
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PointClickCare
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Senior Software Engineer - Data Infrastructure
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United States , San Francisco
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180000.00 - 270000.00 USD / Year
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Plaid
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Senior Director - Data Engineering & Machine Learning
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Canada
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Modus Create
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Software Engineer, Data Infrastructure
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United States , San Francisco; New York
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149000.00 - 350000.00 USD / Year
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Figma
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Senior Software Engineer - Data Integration & JVM Ecosystem
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Germany
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ClickHouse
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Software Engineer - Data Engineering
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United States , Chicago
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130000.00 USD / Year
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AKUNA CAPITAL
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Big Data Scala Engineering Developer
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India , Pune; Chennai
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Citi
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Big Data Engineering Developer
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India , Pune; Chennai
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Citi
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Principal Data Engineer
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United States , San Francisco; Seattle; Austin
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168700.00 - 271100.00 USD / Year
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Atlassian
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Senior Principal Data Engineer
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United States , San Francisco
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Atlassian
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Data Engineer
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Spain , Madrid
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Inetum
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Principal Data Engineer
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United States , San Francisco; Mountain View
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168700.00 - 271100.00 USD / Year
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Atlassian
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Principal Data Engineer
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United States , San Francisco
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168700.00 - 271100.00 USD / Year
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Atlassian
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Sr. Software Engineer - Data Assets
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United States , San Francisco
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6sense
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Data Engineer
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United States , Bethesda
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Robert Half
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Big Data Engineer
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India , Pune
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Citi
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Data Engineer
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United States , Miami
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Robert Half
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Discover and apply for Data Engineer - Python and Spark jobs, a critical role at the heart of modern data-driven organizations. Data Engineers are the architects and builders of the data infrastructure, creating robust pipelines that transform raw, unstructured information into clean, reliable, and accessible data for analytics, machine learning, and business intelligence. Professionals in this field are in high demand, as they enable companies to make informed decisions by ensuring data is accurate, timely, and ready for consumption by data scientists and analysts. A typical day for a Data Engineer involves designing, constructing, and maintaining large-scale data processing systems. Common responsibilities include developing ETL (Extract, Transform, Load) or ELT processes, optimizing data workflows for performance and scalability, and ensuring data quality and consistency across diverse sources. They build and manage data warehouses and data lakes, often in cloud environments like AWS, GCP, or Azure. Data Engineers also collaborate closely with data stakeholders to understand requirements and implement solutions that meet both current and future data needs. Proficiency in Python and Apache Spark is fundamental for these jobs. Python is favored for its versatility and rich ecosystem of data libraries, while Spark is essential for distributed data processing on big data sets. Core skills include advanced SQL for complex querying, experience with data modeling and schema design, and a strong understanding of distributed computing principles. Familiarity with workflow orchestration tools like Apache Airflow, along with knowledge of cloud data services and containerization technologies like Docker and Kubernetes, is increasingly standard. Successful candidates usually possess a problem-solving mindset, attention to detail, and the ability to write efficient, production-grade code. Exploring Data Engineer - Python and Spark jobs means pursuing a career focused on building the foundational systems that power insights and innovation. Whether you are an experienced professional or looking to enter the field, these roles offer the opportunity to work on challenging problems and master the technologies that define the future of data. Start your search today to find a position where you can leverage your technical skills to build the data backbone of tomorrow's enterprises.

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