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Backend Engineer - Data Pipeline Jobs

266 Job Offers

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Specialist: Software Engineer
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South Africa , Johannesburg
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Vodafone
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Fullstack Developer Java/Angular
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Belgium , Brussels
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Amaris Consulting
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Junior Fullstack Developer Java/Angular
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Belgium , Brussels
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Amaris Consulting
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Back-End Developer
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Start.io
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System Engineer
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Keyu Tech LLC.
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Senior Software Engineer
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India , Bengaluru
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7EDGE
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Explore a world of opportunity in Backend Engineer - Data Pipeline jobs, a critical and dynamic field at the intersection of software engineering and data infrastructure. Professionals in this role are the architects and builders of the robust, scalable systems that move, process, and prepare vast quantities of data for analysis, machine learning, and application functionality. Their core mission is to design, develop, and maintain the automated workflows that transform raw data into a reliable, accessible resource for an organization. A Backend Engineer specializing in data pipelines typically shoulders a range of key responsibilities. They design and implement ETL (Extract, Transform, Load) or ELT processes, ensuring data is ingested efficiently from diverse sources. A primary focus is on building systems for data processing, which includes tasks like cleansing, aggregation, and enrichment to guarantee high data quality and integrity. These engineers construct scalable backend services and APIs that enable other teams to interact with the processed data. They are also responsible for monitoring pipeline performance, optimizing for efficiency and cost, and implementing robust error handling and data recovery mechanisms to ensure reliability and uptime. To excel in these jobs, a specific skill set is required. Proficiency in programming languages like Python, Java, Scala, or Go is fundamental. Deep expertise in data processing frameworks (e.g., Apache Spark, Apache Beam, Flink) and workflow orchestration tools (e.g., Apache Airflow, Luigi, Prefect) is essential. A strong understanding of cloud platforms (AWS, GCP, Azure) and their data services (S3, BigQuery, Kafka, etc.) is highly typical. Knowledge of database technologies, both SQL (e.g., PostgreSQL) and NoSQL (e.g., Cassandra), along with principles of distributed systems, data modeling, and software engineering best practices (version control, CI/CD, testing) is crucial. Successful candidates usually possess strong problem-solving abilities, a focus on system reliability, and the capacity to collaborate with data scientists, analysts, and other engineering teams. For those passionate about creating the foundational data infrastructure that powers modern data-driven decision-making, Backend Engineer - Data Pipeline jobs offer a challenging and rewarding career path with high demand across numerous industries.

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