Data Processing Analyst

Why Join Us

At Cloudfide, you’ll work where data truly has impact, scale, and purpose. We design and deliver advanced Big Data and cloud-native data platforms for international clients, including major players in retail and Fortune 500.

We process massive datasets, operate fully in the cloud ecosystem, and work with modern technologies across data engineering, cloud platforms, AI, ML, and MLOps.

In this role, you won’t be expected to build platforms from scratch or write production code every day. Instead, you’ll focus on understanding how complex data platform processes work, identifying what can be improved, and helping make technical workflows clearer, faster, and easier to use for Data Engineers.

Opportunity Overview

You will support a long-term engagement focused on analyzing and improving data platform processes used by Data Engineers.The role is process-focused rather than code-focused. Your main goal will be to step into an unfamiliar client environment, understand how existing workflows operate, identify inefficiencies, and propose practical, incremental improvements.

You will work with processes related to environment provisioning, data pipeline setup, ticketing workflows, configurations, internal platforms, and technical documentation.

This is a great opportunity for someone who enjoys working close to data platforms and technical teams, but is more interested in process analysis, usability, documentation, and workflow improvement than hands-on software development.

Your Responsibilities

• Analyzing existing data platform processes related to environment creation and data pipeline setup.
• Going through technical workflows end-to-end from the perspective of a new user.
• Reviewing and working extensively with technical documentation, process descriptions, and internal platform instructions.
• Identifying unnecessary manual steps, repetitive actions, unclear instructions, bottlenecks, and opportunities for simplification.
• Mapping how current processes work and where Data Engineers experience friction.
• Proposing practical improvements that shorten lead times, reduce cognitive load, and improve consistency.
• Supporting incremental process improvements without disrupting existing platform operations.
• Collaborating with Data Engineers, platform teams, and other stakeholders to understand needs, constraints, and dependencies.
• Acting as a bridge between technical platform owners and Data Engineers by representing the user perspective.
• Documenting findings, recommendations, and proposed changes in a clear and structured way.

What We’re Looking For

• Experience or strong interest in data-related processes, data platforms, or technical workflows.
• Background in one of the following areas: Data Analysis, Data Operations, Data Processing, Technical Process Analysis, Business Analysis, or process improvement in technical environments.
• Ability to work comfortably with complex systems, technical documentation, and unfamiliar workflows.
• Strong analytical mindset and attention to detail.
• Ability to independently identify problems, ask the right questions, and propose realistic improvements.
• Clear communication skills, especially when explaining process issues, dependencies, and recommendations.
• Structured, patient, and pragmatic approach to problem-solving.
• Comfort with technical configurations, even if you are not the person implementing them directly.
• Curiosity and willingness to understand how data platform processes work from the user perspective.

Nice to Have

• Familiarity with Databricks - understanding what it is and how it is generally used is enough.
• Experience working with internal platforms, enterprise tools, or regulated environments.
• Understanding of data engineering workflows, data pipelines, or cloud data platforms.
• Experience analyzing user journeys, operational workflows, or technical processes.
• Experience using AI tools for documentation analysis, summarization, knowledge extraction, or process mapping.
• Previous exposure to ticketing systems, approval workflows, or security-heavy enterprise processes.