Extensible Markup Language (XML)
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Back in the late nineties, when the internet was still largely a Wild West of poorly formatted HTML, came a beacon of hope—or so we were told. Extensible Markup Language promised to solve the problem of data transport and storage with a simple idea: define your own tags. It was the lovechild of SGML and HTML, aiming for machine-readability and self-documentation. Quite clever, really, though one does wonder if anyone actually read those verbose XML files.
The reality? XML became a sprawling beast of configuration files, web services contracts, and data exchange formats. While it delivered on interoperability, it also delivered a hefty dose of parsing overhead and verbosity. JSON, the scrappy upstart, quickly stole its lunch as the preferred data format for the web. Today, XML persists in legacy systems and certain enterprise applications—a testament to sunk costs and the enduring power of established standards. It's still there, quietly humming along, proving that sometimes, "good enough" is good enough indeed.
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Jobs in using Extensible Markup Language (XML) for but please no
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analyst
Data Analyst @ planet-pharma
US | 2025-12-28
An ostensibly Data Analyst role that reads like a cross between analytics strategy and light data engineering. You’ll drive advanced analytics for Global Operations, automate reporting, and build...
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Data Analytics, Data Collection, Data Science, Analytics, Dashboard, Management, BI, Computer Science, Python, Pandas, NumPy, SQL, API, XML, Google Sheets, Cloud Computing, Snowflake, GCP, AWS, RDBMS, R, Git, CI/CD, AI/ML | ||
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analyst
Data Analyst- Orion @ consultnet
US | 2025-12-26
A six-month contract role requiring extensive financial industry experience, notably with Orion and Black Diamond, focusing on data conversion, reconciliation, and automation within portfolio...
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C, ETL/ELT, Management, XML, Python, SQL, Jira | ||
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promoted
BigQuery Cost Optimization Guide by Masthead DataThe BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of... |
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data engineer
Director, Principal Data Architect @ tiffany-and-co
US | 2025-12-26
This role is a highly demanding and complex position requiring deep expertise in GCP data architecture, DevOps, and cloud-native engineering. The candidate must lead platform enablement, mentor...
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Management, GCP, Analytics, Cloud Computing, Big Data, AI/ML, Data Streaming, Data Lake, DWH, Data Engineering, AWS, Azure, SaaS, Data Management, DevOps, CI/CD, Marketing, Agile/Scrum, BigQuery, Cloud Composer, Fivetran, Power BI, Dataiku, SQL, ETL/ELT, Jira, Azure DevOps, GitHub, Computer Science, Cyber Security, Data Quality, API, Parquet, Avro, JSON, XML, CSV, dbt, Python, Data Science |
