Agile/Scrum

project management, software development, methodology
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Agile/Scrum: the tech world’s favorite buzzword cocktail. Born out of the Agile Manifesto in 2001, Scrum became the go-to framework for teams tired of bloated waterfall
methods. In theory, it's all about adaptability, collaboration, and delivering incremental value. In reality? Mostly just stand-up meetings that no one really stands for
anymore. Competing with Kanban and other agile frameworks, Scrum’s claim to fame is its structured approach: sprints, backlogs, and the coveted daily scrum. Great for keeping
teams "aligned," or at least pretending to be. But let’s face it—Scrum can turn into a bureaucratic mess if not done right (looking at you, cargo cult Scrum Masters).

Still, in its current state, it’s used everywhere from startups to massive enterprises trying to be 'nimble'—despite drowning in Jira tickets. Key differentiator? Scrum loves
process, but not too much process. Just enough to keep you sprinting in circles.

Used together with Agile/Scrum

Additional Resources

Agile Manifesto Agile Data Modelling Agile Data Warehouse Design Scrum: An Honest Ad
Jobs (this month)

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Jobs in using Agile/Scrum for but please no

data engineer

Project Manager │ プロジェクトマネージャー @ persol-career-brs

JP | 2025-12-28 | JPY 8000000 - 15000000 / year
Project Manager for IoT and cloud-based digital transformation at a giant IT services firm, Tokyo-based with remote options. You’ll lead IoT cloud platform development for a world-class... read more »
Cloud Computing, IoT, AI/ML, Management, Agile/Scrum, Azure, SQL, Data Lake, Synapse, Analytics, Databricks
data engineer

Senior Data Management Professional - Data Engineering - APAC New Issues, Tokyo @ bloomberg

JP | 2025-12-27
Senior Data Management Professional - Data Engineering at Bloomberg in Tokyo demands a bilingual, technically hands‑on lead who can cradle the corporate bonds pipeline from ingestion to... read more »
Data Management, Data Engineering, Analytics, BI, ETL/ELT, DataViz, Python, Data Quality, Management, Data Science, AI/ML, Qlik, Superset, Agile/Scrum
promoted

The Fundamentals of Analytics Engineering

The Fundamentals of Analytics Engineering gives a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering. It's a book that teaches concepts and best practices, not just tools and technologies.

Learn More
data engineer

Senior Data Engineer @ bain-and-company

JP | 2025-12-26
Senior Data Engineer in Bain’s AIS Data Engineering within the AI, Insights & Solutions team. You’ll design, build and deploy data solutions for production-scale client ecosystems, and own the... read more »
AI/ML, Analytics, Management, Data Engineering, Data Science, Cloud Computing, Python, Scala, C, C++, Java, Go, Airflow, Beam, SQL, NoSQL, Databricks, PostgreSQL, SQL Server, Oracle, MySQL, Redis, MongoDB, ELK, Hive, Apache HBase, Teradata, Cassandra, Redshift, AWS, Azure, GCP, Kubernetes, Terraform, DevOps, CI/CD, GitHub, Computer Science, Agile/Scrum