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Data Engineer - Python and Spark Jobs

140 Job Offers

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Big Data & Scala Engineer
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Portugal , Porto
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We Are Meta
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Senior Product Manager - Privacy Experiences
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United States
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Mozilla
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Tech Lead - Pretraining Team, Wayve Foundation Model
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United States , Sunnyvale
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Wayve
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Senior Software Engineer - Wayve Foundation Model
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Canada , Vancouver
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Wayve
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Senior Distributed Systems & Detection Engineer
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Portugal , Lisboa
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Precise
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Lead Data Solution Architect
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Singapore , Singapore
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Thoughtworks
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Senior Backend Engineer - Recommendations Systems (ML)
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Germany; United Kingdom , Berlin; London
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SoundCloud
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Sr. Distinguished Software Engineer (Anti-Money Laundering)
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United States , McLean; Richmond; New York
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286200.00 - 392000.00 USD / Year
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Capital One
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Specialist Integration Software Engineer
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India , Hyderabad
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Amgen
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Software Engineer
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United States , Annapolis Junction
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2HB
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Staff Software Engineer, Social Graph
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United States , San Francisco
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181000.00 - 271000.00 USD / Year
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GoFundMe
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Full Stack Developer
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Romania , Bucharest
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Connections Tech
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Senior Backend Engineer
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Taiwan , Taipei
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Taboola
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Senior Software Engineer - Wayve Foundation Model
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Canada , Vancouver
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Wayve
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Principal Engineer, Model Dev Platform
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United States , Sunnyvale
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Wayve
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Data Architect
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Canada , Mississauga
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120800.00 - 170800.00 USD / Year
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Citi
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Business Analyst
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India , Bangalore
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Start.io
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Machine Learning Engineer
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United States , New York or Boston
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138250.00 - 197500.00 USD / Year
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Spotify
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Lead Full Stack Developer
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India , Pune
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Citi
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Lead Full stack Developer
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India , Pune
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Citi
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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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