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Data Engineer - Python and Spark Jobs

3 Job Offers

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Real-Time Data Engineer (Flink / Spark Streaming)
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Join Bright Vision Technologies as a Real-Time Data Engineer. Design and build event-driven data pipelines using Apache Flink, Spark Streaming, and Kafka. This role requires 3-5 years of real-time experience, US project exposure, and offers nationwide relocation with H-1B sponsorship for the 2026...
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United States
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Not provided
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Bright Vision Technologies
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Until further notice
New
Real-Time Data Engineer (Flink / Spark Streaming)
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Join Bright Vision Technologies as a Real-Time Data Engineer. Design and build event-driven streaming pipelines using Apache Flink, Spark, and Kafka. This role requires 3-5 years of real-time experience, cloud platform expertise, and offers H-1B sponsorship for the 2026 quota. Relocation within t...
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United States
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Not provided
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Bright Vision Technologies
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Until further notice
Data Engineer (Spark)
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Join Addepto as a Data Engineer (Spark) and build scalable AI solutions for global clients. Leverage your 4+ years in Big Data, Python/Java/Scala, and cloud tech like Spark, Kafka, and AWS. Enjoy remote flexibility from key Polish cities while growing in a passionate AI team with top-tier projects.
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Poland , Warsaw; Cracow; Wroclaw; Bialystok
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15120.00 - 31920.00 PLN / Month
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Addepto sp. z o.o.
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Until further notice
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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