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Back in the day, version control was largely the domain of Git, necessitating separate tools for issue tracking, CI/CD, and all the other delightful complexities of software development. Then came GitLab, promising to be the single application to rule them all – a complete DevOps platform. Quite clever, really, though one does wonder if striving for total domination wasn’t a touch ambitious.

In practice, GitLab delivers on much of that promise, offering a remarkably integrated suite. It’s robust, feature-rich, and undeniably powerful. However, that very breadth can be overwhelming; it’s a full operating system for your code, demanding significant configuration and upkeep. Compared to the more modular approach of, say, pairing GitHub with Jenkins or CircleCI, GitLab is an all-in-one solution that appeals to those who crave control… and have the bandwidth to wield it. Today, it’s a popular choice for organizations seeking end-to-end visibility and control over their development lifecycle, though a healthy contingent still prefers the flexibility of best-of-breed tools.

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Jobs in using GitLab for but please no

analytics engineer

(Senior) Consultant Data Transformation & Migration @ kpmg-nederland

NL | 2025-12-27
The role at KPMG’s Powered Data team is positioned as a technical consultant focused on data transformation and migration, with a mandate to drive innovation and support organizational change. The... read more »
ERP, SAP, Microsoft, Data Modelling, Data Management, Java, SQL, Python, DAX, GitLab
analytics engineer

Ingénieur Data & Information Protection Microsoft (H/F) @ devoteam-cyber-trust

FR | 2025-12-27
Devoteam’s Microsoft-centric Data & Information Protection Engineer role is a governance and security engineer with a data tilt. It expects you to own data governance, GDPR/CCPA compliance, and... read more »
Cloud Computing, AI/ML, AWS, Microsoft, Fabric, GDPR/CCPA, Azure, Data Lakehouse, Power BI, Databricks, SQL, Synapse, ADF, Snowflake, SAP, GitLab
promoted

O'Reilly: Building AI Agents with Model Context Protocol (MCP)

Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.

FR | 2025-12-26
An Analytics Engineer role at Crédit Agricole d’Ile-de-France involves designing data models and building scalable ELT architectures, with a unique focus on collaboration across various... read more »
Marketing, Analytics, ETL/ELT, dbt, PySpark, CI/CD, GitLab, Airflow, BI, Big Data, Data Engineering, Spark, Data Modelling, Python, SQL
analytics engineer

【1496】_TE_【東京勤務】Honda SDV開発におけるデータ基盤エンジニア/データサイエンティスト @ honda

JP | 2025-12-25 | JPY 5900000 - 1090000 / year
Honda is fervently pursuing its Software Defined Vehicle (SDV) initiative, seeking a data engineer to architect and construct a robust data foundation from their labyrinthine data source web.... read more »
AI/ML, ETL/ELT, Python, SQL, JavaScript, C, AWS, Redshift, AWS Glue, AWS Lambda, GCP, BigQuery, Dataflow, Azure, Synapse, Databricks, Docker, Kubernetes, Jenkins, GitHub, GitLab, Jira, Confluence, Tableau, Power BI, Superset, Pandas, TensorFlow, PyTorch, GenAI, R, CI/CD